Research Grade 7: £40,855 - £46,913 per annum with a discretionary range to £51,059 per annum
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Mathematical, Physical and Life Sciences (MPLS)
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We currently have a fantastic opportunity for an experienced and motivated individual to join our dedicated, professional and friendly Statistical Consulting Unit at the Department of Statistics. The (Senior) Statistical Consultant will play a key role in end-to-end provision of the Department's Statistical Consulting Unit, which may include: liaising with clients across a range of sectors to understand their needs in the domain of statistics and data analysis; formulating and providing bespoke solutions to their statistical problems; interpreting and delivering the results of the statistical analysis, as well as developing appropriate code; contributing to the design and delivery of training when required. The successful (Senior) Statistical Consultant will be expected to engage with a broad range of stakeholders across private and public sectors to promote the Department's Statistical Consultancy Services and proactively identify new opportunities for service provision. In addition to targeting external clients, the postholder will provide statistical advice and consultancy to University staff and researchers, and actively engage with other Departments, acting as an ambassador for good statistical practice. A doctorate (or have equivalent research or professional experience) in Statistics or a related field with post-qualification statistical client- facing consultancy experience is essential for this role. In addition, the (Senior) Statistical Consultant will have a broad knowledge of applied statistics and statistical software, with evidence of an ability to communicate engagingly both in writing and orally, and to explain statistical concepts to non-technical clients and audiences. Strong track record of projects and consultancy activities with other Departments of the University of Oxford and/or external clients is a must. It would be desirable to have knowledge and experience of applied artificial intelligence/machine learning and a chartered Statistician (CStat) qualification. **This role is advertised at a grade 8; however, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be made to a Statistical Consultant role at grade 7 ( £38,674- £46,913 per annum with a discretionary range to £51,059) with the responsibilities adjusted accordingly. This would be discussed with applicants at interview/appointment where appropriate.** **Only applications received before 12.00 noon (UK time) on Monday 30th June can be considered. Interviews are to be held on Thursday 24th July.**
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We invite applications for a Postdoctoral Research Associate to join a research project funded by an EPSRC grant. The position is offered on a fixed-term basis until 31 August 2026, with a maximum duration of ten months (10 months), and is full-time. Reporting to Prof. Gesine Reinert, the post holder will be a member of a research group with responsibility for carrying out research in the area of developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings. We proudly hold a Race Equality Charter Bronze Award and a departmental Athena SWAN Silver Award, which guide our progress towards advancing racial and gender equality. As part of our commitment to openness, inclusivity and transparency, we would particularly welcome applications from women and black and minority ethnic candidates, who are currently under-represented in positions of this type at Oxford. Please direct informal enquiries to Prof. Gesine Reinert (reinert@stats.ox.ac.uk) quoting vacancy reference 178517. Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as outlined in full in the job description. You will be required to upload a statement setting out how you meet the selection criteria, a curriculum vitae including a list of publications, a statement of research interests, and the contact details of two referees as part of your online application. (NOTE: Applicants are responsible for contacting their referees and making sure that their reference letters are sent directly to hr@stats.ox.ac.uk , by the closing date – quoting the reference number and job title). Only applications received before 12.00 noon UK time on June 13, 2025 can be considered. Interviews are anticipated to be held in the week starting 7 July 2025.
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Department of Statistics, 24-29 St Giles’, Oxford, OX1 3LB
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We invite applications for a Postdoctoral Research Associate to join a research project funded by an EPSRC grant. The position is offered on a fixed-term basis until 31 August 2026, with a maximum duration of ten months (10 months), and is full-time. Reporting to Prof. Gesine Reinert, the post holder will be a member of a research group with responsibility for carrying out research in the area of developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings. We proudly hold a Race Equality Charter Bronze Award and a departmental Athena SWAN Silver Award, which guide our progress towards advancing racial and gender equality. As part of our commitment to openness, inclusivity and transparency, we would particularly welcome applications from women and black and minority ethnic candidates, who are currently under-represented in positions of this type at Oxford. Please direct informal enquiries to Prof. Gesine Reinert (reinert@stats.ox.ac.uk) quoting vacancy reference 178517. Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as outlined in full in the job description. You will be required to upload a statement setting out how you meet the selection criteria, a curriculum vitae including a list of publications, a statement of research interests, and the contact details of two referees as part of your online application. **(NOTE: Applicants are responsible for contacting their referees and making sure that their reference letters are sent directly to hr@stats.ox.ac.uk , by the closing date – quoting the reference number and job title).** **Only applications received before 12.00 noon UK time on June 13, 2025 can be considered. Interviews are anticipated to be held in the week starting 7 July 2025.**
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_________________________________________________________________________ Job Description Job title (Senior) Statistical Consultant Division Mathematical, Physical and Life Sciences Department Statistics Location 24-29 St Giles’, Oxford, OX1 3LB Grade and salary Grade 8: £48,235 - £57,255 (with a discretionary range to £62,407) per annum Hours Full time Contract type Permanent Reporting to Senior Academic with relevant expertise, currently Prof Windmejier Vacancy reference 179779 Additional information This role is advertised at a grade 8; however, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be made to a Statistical Consultant role at grade 7 (£38,674£46,913 per annum with a discretionary range to £51,059) with the responsibilities adjusted accordingly. This would be discussed with applicants at interview/appointment where appropriate. Job description The role The post holder will play a key role in end-to-end provision of the Department's Statistical Consulting Unit, which may include: liaising with clients across a range of sectors to understand their needs in the domain of statistics and data analysis; formulating and providing bespoke solutions to their statistical problems; interpreting and delivering the results of the statistical analysis, as well as developing appropriate code; contributing to the design and delivery of _________________________________________________________________________ training when required. Typical requests may involve developing statistical analysis plans and performing power calculations; reviewing statistical output, identifying potential problems and advising on/applying appropriate statistical methods (e.g. descriptive and correlational analysis; generalised linear models, structural equation models, multilevel models, non-linear models); experimental and observational study design; measurement scale. If possible, we would like to hire someone with artificial intelligence/machine learning skills. The postholder will be expected to engage with a broad range of stakeholders across private and public sectors to promote the Department's Statistical Consultancy Services and proactively identify new opportunities for service provision. In addition to targeting external clients, the postholder will provide statistical advice and consultancy to University staff and researchers, and actively engage with other Departments, acting as an ambassador for good statistical practice. The post holder will report to a senior academic with relevant expertise, currently Prof Windmejier. They will work closely with the other senior statistical consultant in the unit on strategic planning and development of the service’s activities. The post holder will mentor students and postdoctoral researchers undertaking consultancy. External consultancy contracts will be managed in conjunction with Oxford University Innovation. The post holder will contribute to the academic life of the department, including advising on overall scientific and management matters and sitting on Departmental committees. Responsibilities/duties • • • • • Provide statistical advice, analysis and interpretation of results to external organisations and researchers from other University of Oxford Departments; deliver high-quality reports and client presentations. Work closely with the other senior consultant in the unit to further the growth of the Department's provision of statistical consultancy services, managing and monitoring team resources and income flows, and helping determine the service’s strategic direction over the next three to five years. Support with the development and delivery of teaching on statistical consultancy and the use of statistics to both internal and external clients across a range of disciplines, when required. Promote and facilitate excellence in statistical practice across the University, including conducting pro bono work for central University units. Promote the Department's consultancy services nationally and internationally; represent the Department at client-facing meetings and engage with sponsors, stakeholders, national agencies, professional bodies and appropriate networks. _________________________________________________________________________ • • • • • Work with Oxford University Innovation to manage and deliver contracts with external clients; liaise with clients and proactively identify new opportunities and potential projects. Develop ideas for generating further income based on outcomes of consultancy. Serve on Departmental committees, advising on scientific and management matters for the Department; be involved in the Department's outreach and public engagement activities. Provide mentoring and supervision for students involved in consultancy services. Participate in the administration of the Department as and when requested by the Head of Department. Selection criteria Essential • • • • • • • Hold a Doctorate (or have equivalent research or professional experience) in Statistics or a related field with post-qualification statistical client-facing consultancy experience Possess broad knowledge of applied statistics and statistical software Evidence of an ability to communicate engagingly both in writing and orally, and to explain statistical concepts to non-technical clients and audiences Excellent interpersonal skills Strong track record of projects and consultancy activities with other Departments of the University of Oxford and/or external clients. (An appointment at Grade 7 could be made on the basis of less experience of projects and/or consultancy.) Strong programming skills A commitment to promoting equality, diversity and inclusion in statistics. Desirable • • • • • Knowledge and experience of applied artificial intelligence/machine learning Experience of collaborations at national and international level Chartered Statistician (CStat) qualification Expertise in using R /or Stata. Additional software expertise, e.g. in Python, is desirable Experience of managing a budget About the University of Oxford Welcome to the University of Oxford. We aim to lead the world in research and education for the benefit of society both in the UK and globally. Oxford’s researchers engage with academic, commercial and cultural partners across the world to stimulate high-quality research and enable innovation through a broad range of social, policy and economic impacts. _________________________________________________________________________ We believe our strengths lie both in empowering individuals and teams to address fundamental questions of global significance, while providing all our staff with a welcoming and inclusive workplace that enables everyone to develop and do their best work. Recognising that diversity is our strength, vital for innovation and creativity, we aspire to build a truly diverse community which values and respects every individual’s unique contribution. While we have long traditions of scholarship, we are also forward-looking, creative and cuttingedge. Oxford is one of Europe's most entrepreneurial universities. Income from external research contracts in 2016/17 exceeded £564m and we rank first in the UK for university spin-outs, with more than 130 companies created to date. We are also recognised as leaders in support for social enterprise. Join us and you will find a unique, democratic and international community, a great range of staff benefits and access to a vibrant array of cultural activities in the beautiful city of Oxford. For more information, please visit www.ox.ac.uk/about/organisation. The Department of Statistics The Department of Statistics at Oxford is a world-leading centre for research with a broad portfolio that covers pure theory, the development of innovative methods to analyse and understand data, and their applications to scientific and societal problems. Research is loosely structured around seven interconnected research groups: Statistical Theory and Methodology; Computational Statistics and Machine Learning; the Oxford Protein Informatics Group; Probability; Statistical Genetics and Epidemiology; Econometrics and Population Statistics; and Computational Biology and Bioinformatics. The Department has recently undergone a period of rapid expansion, growing from 21 submitted researchers in the 2014 Research Excellence Framework exercise to 32 in REF 2021. The Department relocated to a newly renovated building on St Giles’ in the heart of the University of Oxford in 2015. The building provides state-of-the-art teaching facilities and modern space to facilitate collaboration and integration, creating a highly visible centre for Statistics in Oxford. Since moving to St Giles’, Faculty have secured over £14m in research funding from a variety of funders including UKRI, the Wellcome Trust, the European Commission, NIH, and industrial partners from sectors ranging from services to pharma. Research from the Department of Statistics and the Mathematical Institute in Oxford was submitted together for the UK’s most recent national research assessment exercise, the Research Excellence Framework (REF) 2021. Overall, 78% of our submission was judged to be 4* (the highest score available, for research quality that is world-leading in terms of originality, significance, and rigour). This outstanding result is a testament to the breadth, quality and impact of the research produced by colleagues in our two departments, and the outstanding environment in which they work, supported by our excellent professional services staff. _________________________________________________________________________ The Department’s research excellence has been recognised both collectively, through success in REF 2021, and individually. Alison Etheridge was appointed Dame Commander of the Order of the British Empire in the 2025 New Years Honours. Awards include Fellowships of the Royal Society to Christl Donnelly and Alison Etheridge; Fellowship of the British Academy to Frank Windmeijer; FMedSci and the Zoological Society of London’s Frink Award to Christl Donnelly; the Royal Statistical Society Guy Medal in Bronze to Chris Holmes; the Weldon Memorial Prize, the Francis Crick Prize Lecture, and the Genetics Society Balfour Prize to Simon Myers. Alison Etheridge, Christina Goldschmidt and Gesine Reinert are all Fellows of the Institute of Mathematical Statistics, and Alison Etheridge is a former President. Alison Etheridge was also elected as a member of the American Academy of Arts and Sciences. The Department is home to Oxford University Statistical Consulting, which provides comprehensive statistical consultancy services to both internal departments and external businesses. It operates across a wide range of sectors, and offers experience in all aspects of data-based research. The service includes two Research Software Engineers who take new and existing software platforms from the Oxford Protein Informatics Group, and provide support to industry to maximise their impact. The Department of Statistics offers an undergraduate degree (BA or MMath) in Mathematics and Statistics and an MSc in Mathematical Science (OMMS), both joint with the Mathematical Institute, and an MSc in Statistical Science, as well as a lively and stimulating environment for postgraduate researchers (DPhil or MSc by Research). The Department is involved in five Centres for Doctoral Training (CDTs): the EPSRC CDT in Modern Statistics and Statistical Machine Learning (led by Imperial), the EPSRC CDT in Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research, the EPSRC CDT in Mathematics of Random Systems (with the Mathematical Institute and Imperial), the EPSRC CDT in Health Data Science (with the Big Data Institute) and the recently launched Fundamentals of AI CDT which is funded by the Ellison Institute of Technology. The Department is also part of the National Academy for PhD Training in Statistics, which provides training in fundamental areas of Statistics and Applied Probability. Our graduate students go on to varied careers, the most popular being academia (45%) and the technology (nearly 30%) and finance sectors. The Department maintains well-established connections with interdisciplinary centres such as the Wellcome Centre for Human Genetics and the Big Data Institute. Many Faculty have associations with the Alan Turing Institute (the Turing), the UK’s national centre for data science, in which Oxford is a founding partner. The Department also enjoys close links with the Ellison Institute of Technology, a newly established company which combines cutting-edge research and commercial capability, to drive scientific breakthroughs through creating sustainable companies. Chris Holmes, Professor of Biostatistics, is the Director of AI for EIT, and Gil McVean, Principal Scientist for the Pathogen Progamme, also has a joint appointment with the Department of Statistics as Professor of Statistical Genetics. _________________________________________________________________________ The Department of Statistics holds a silver Athena Swan award to recognise advancement of gender equality: representation, progression and success for all. For more information please visit: www.stats.ox.ac.uk. The Mathematical, Physical and Life Sciences Division The Mathematical, Physical, and Life Sciences (MPLS) Division is one of the four academic divisions of the University. Oxford is widely recognised as one of the world's leading science universities. The disciplines within the MPLS Division regularly appear at the highest levels in world rankings and the REF 2021 results highlighted the quality of its research, the environment in which it is conducted, and the impact it has. The MPLS Division is home to the non-medical sciences at Oxford and its 9 academic departments span the full spectrum of the mathematical, computational, physical, engineering and life sciences, and undertake both fundamental research and cutting-edge applied work. Research in MPLS tackles major societal and technological challenges – whether developing new energy solutions or improved cancer treatments, understanding climate change processes, or helping to preserve biodiversity, and is increasingly focused on key interdisciplinary issues. MPLS Division also includes Begbroke Science Park – the only science park wholly owned and managed by Oxford University. It stands at the forefront of innovative collaboration; a place where science and industry meet. We collaborate closely with colleagues in Oxford across the medical sciences, social sciences and humanities, and with other universities, research organisations and industrial partners across the globe in pursuit of innovative research geared to address critical and fundamental scientific questions. The disciplines within the MPLS Division appear at the highest levels in world rankings, with Oxford’s mathematical, physical and life sciences research regularly identified as one of the most significant recipients of grant funding in Europe. MPLS is proud to be the home of some of the most creative and innovative scientific thinkers and leaders working in academe. Our senior researchers have been awarded some of the most significant scientific honours, including the most recent award of a Nobel Prize for Physics 2020 to Sir Roger Penrose. Within MPLS we are as focused on the next generation as we are on those who have gone before, having a strong tradition of attracting and nurturing the very best early career researchers who regularly secure prestigious fellowships and faculty positions. MPLS continues in its work to support diversity in its staffing, seeing that it will bring benefits to everyone. All academic departments in the Division hold Athena Swan Awards (The Athena Swan Charter encourages and recognises commitment to advancing the careers of women in science, technology, engineering, maths and medicine employment in higher education and research.) _________________________________________________________________________ We have around 7,400 full and part-time students (including approximately 3,500 graduate students) and play a major role in training the next generation of leading scientists. Oxford's international reputation for excellence in teaching is reflected in its position at the top of the major league tables and subject assessments. MPLS academics educate students of high academic merit and potential from all over the world. Through a mixture of lectures, practical work and the distinctive college tutorial system, students develop their ability to solve major mathematical, scientific and engineering problems. MPLS is dedicated to bringing the wonder and potential of science to the attention of audiences far beyond the world of academia. We have a strong commitment to supporting public engagement in science through initiatives including the Oxford Sparks portal and Science Together programme. These are complemented by a large variety of outreach activities; these are crucial activities given so many societal and technological issues demand an understanding of the science that underpins them. We also bring the potential of our scientific efforts forward for practical and beneficial application to the real world and our desire, aided by the work of Oxford University Innovation and Oxford Science Enterprises, is to link our best scientific minds with industry and public policy makers. For more information about the MPLS division, please visit: www.mpls.ox.ac.uk How to apply Before submitting an application, you may find it helpful to read the ‘Tips on applying for a job at the University of Oxford’ document, at www.ox.ac.uk/about/jobs/supportandtechnical/. If you would like to apply, click on the Apply Now button on the ‘Job Details’ page and follow the on-screen instructions to register as a new user or log-in if you have applied previously. Please provide details of two referees and indicate whether we can contact them now. You will also be asked to upload a CV and a supporting statement. The supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants). Your application will be judged solely on the basis of how you demonstrate that you meet the selection criteria stated in the job description. Please upload all documents as PDF files with your name and the document type in the filename. All applications must be received by midday on the closing date stated in the online advertisement. Information for priority candidates _________________________________________________________________________ A priority candidate is a University employee who is seeking redeployment because they have been advised that they are at risk of redundancy, or on grounds of ill-health/disability. Priority candidates are issued with a redeployment letter by their employing departments. If you are a priority candidate, please ensure that you attach your redeployment letter to your application (or email it to the contact address on the advert if the application form used for the vacancy does not allow attachments) Should you experience any difficulties using the online application system, please email recruitment.support@admin.ox.ac.uk. Further help and support are available from www.ox.ac.uk/about_the_university/jobs/support/. To return to the online application at any stage, please go to: www.recruit.ox.ac.uk. Please note that you will be notified of the progress of your application by automatic emails from our e-recruitment system. Please check your spam/junk mail regularly to ensure that you receive all emails. Important information for candidates Data Privacy Please note that any personal data submitted to the University as part of the job application process will be processed in accordance with the GDPR and related UK data protection legislation. For further information, please see the University’s Privacy Notice for Job Applicants at: www.admin.ox.ac.uk/councilsec/compliance/gdpr/privacynotices/job/. The University’s Policy on Data Protection is available at: www.admin.ox.ac.uk/councilsec/compliance/gdpr/universitypolicyondataprotection/. The University’s policy on retirement The University operates an Employer Justified Retirement Age (EJRA) for all academic posts and some academic-related posts. The University has adopted an EJRA of 30 September before the 69th birthday for all academic and academic-related staff in posts at grade 8 and above. The justification for this is explained at: www.admin.ox.ac.uk/personnel/end/retirement/acrelretire8+/. For existing employees, any employment beyond the retirement age is subject to approval through the procedures: www.admin.ox.ac.uk/personnel/end/retirement/acrelretire8+/. There is no normal or fixed age at which staff in posts at grades 1–7 have to retire. Staff at these grades may elect to retire in accordance with the rules of the applicable pension scheme, as may be amended from time to time. Equality of Opportunity _________________________________________________________________________ Entry into employment with the University and progression within employment will be determined only by personal merit and the application of criteria which are related to the duties of each particular post and the relevant salary structure. In all cases, ability to perform the job will be the primary consideration. No applicant or member of staff shall be discriminated against because of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. _________________________________________________________________________ Benefits of working at the University Employee benefits University employees enjoy 38 days’ paid holiday, generous pension schemes, travel discounts, and a variety of professional development opportunities. Our range of other employee benefits and discounts also includes free entry to the Botanic Gardens and University colleges, and discounts at University museums. See www.admin.ox.ac.uk/personnel/staffinfo/benefits. University Club and sports facilities Membership of the University Club is free for all University staff. The University Club offers social, sporting, and hospitality facilities. Staff can also use the University Sports Centre on Iffley Road at discounted rates, including a fitness centre, powerlifting room, and swimming pool. See www.club.ox.ac.uk and www.sport.ox.ac.uk/oxford-university-sports-facilities. Information for staff new to Oxford If you are relocating to Oxfordshire from overseas or elsewhere in the UK, the University's Welcome Service website includes practical information about settling in the area, including advice on relocation, accommodation, and local schools. See www.welcome.ox.ac.uk. There is also a visa loan scheme to cover the costs of UK visa applications for staff and their dependents. See www.admin.ox.ac.uk/personnel/permits/reimburse&loanscheme/. Family-friendly benefits With one of the most generous family leave schemes in the Higher Education sector, and a range of flexible working options, Oxford aims to be a family-friendly employer. We also subscribe to My Family Care, a service that provides practical advice and support for employees who have caring responsibilities. The service offers a free telephone advice line, and the ability to book emergency back-up care for children, adult dependents and elderly relatives. See www.admin.ox.ac.uk/personnel/staffinfo/benefits/family/mfc/. Childcare The University has excellent childcare services, including five University nurseries as well as University-supported places at many other private nurseries. For full details, including how to apply and the costs, see www.admin.ox.ac.uk/childcare/. Disabled staff We are committed to supporting members of staff with disabilities or long-term health conditions. For further details, including information about how to make contact, in confidence, with the University’s Staff Disability Advisor, see www.admin.ox.ac.uk/eop/disab/staff. Staff networks _________________________________________________________________________ The University has a number of staff networks including the Oxford Research Staff Society, BME staff network, LGBT+ staff network and a disabled staff network. You can find more information at www.admin.ox.ac.uk/eop/inpractice/networks/. The University of Oxford Newcomers' Club The University of Oxford Newcomers' Club is an organisation run by volunteers that aims to assist the partners of new staff settle into Oxford, and provides them with an opportunity to meet people and make connections in the local area. See www.newcomers.ox.ac.uk.
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We currently have a fantastic opportunity for an experienced and motivated individual to join our dedicated, professional and friendly Statistical Consulting Unit at the Department of Statistics. The (Senior) Statistical Consultant will play a key role in end-to-end provision of the Department's Statistical Consulting Unit, which may include: liaising with clients across a range of sectors to understand their needs in the domain of statistics and data analysis; formulating and providing bespoke solutions to their statistical problems; interpreting and delivering the results of the statistical analysis, as well as developing appropriate code; contributing to the design and delivery of training when required. The successful (Senior) Statistical Consultant will be expected to engage with a broad range of stakeholders across private and public sectors to promote the Department's Statistical Consultancy Services and proactively identify new opportunities for service provision. In addition to targeting external clients, the postholder will provide statistical advice and consultancy to University staff and researchers, and actively engage with other Departments, acting as an ambassador for good statistical practice. A doctorate (or have equivalent research or professional experience) in Statistics or a related field with post-qualification statistical client-facing consultancy experience is essential for this role. In addition, the (Senior) Statistical Consultant will have a broad knowledge of applied statistics and statistical software, with evidence of an ability to communicate engagingly both in writing and orally, and to explain statistical concepts to non-technical clients and audiences. Strong track record of projects and consultancy activities with other Departments of the University of Oxford and/or external clients is a must. It would be desirable to have knowledge and experience of applied artificial intelligence/machine learning and a chartered Statistician (CStat) qualification. This role is advertised at a grade 8; however, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be made to a Statistical Consultant role at grade 7 (£38,674- £46,913 per annum with a discretionary range to £51,059) with the responsibilities adjusted accordingly. This would be discussed with applicants at interview/appointment where appropriate. Only applications received before 12.00 noon (UK time) on Monday 30th June can be considered. Interviews are to be held on Thursday 24th July.
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_________________________________________________________________________ Job Description Job title Postdoctoral Research Associate in Statistics Division Mathematical, Physical and Life Sciences Department Statistics Location 24-29 St Giles’, Oxford, OX1 3LB Grade and salary Grade 7: £40,855 - £46,913 per annum (with a discretionary range to £51,059 per annum) Hours Full time Contract type Fixed-term for 10 months, ending no later than 31 August 2026 Reporting to Prof Gesine Reinert Vacancy reference 179814 Research topic Characterising Models for Networks Principal Investigat or / supervisor Prof Gesine Reinert Project web site Funding partner Recent publicatio ns https://www.stats.ox.ac.uk/~reinert/CHARMNET.html The funds supporting this research project are provided by EPSRC https://scholar.google.com/citations?hl=en&user=2gvyN5oAAAAJ&view_op=list_works&so rtby=pubdate _________________________________________________________________________ Job description Overview of the role The post holder will report to Prof Gesine Reinert who is the Principal Investigator on the project. The post holder is a member of a research group with responsibility for carrying out research in the area of developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project students and PhD students. Responsibilities/duties • Manage own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines • Adapt existing and develop new research methodologies and materials • Prepare working theories and analyse qualitative and/or quantitative data from a variety of sources, reviewing and refining theories as appropriate • Contribute ideas for new research projects • Develop ideas for generating research income, and present detailed research proposals to senior researchers • Collaborate in the preparation of research publications • Present papers at conferences or public meetings • Act as a source of information and advice to other members of the group on methodologies or procedures • Represent the research group at external meetings/seminars, either with other members of the group or alone • Carry out collaborative projects with colleagues in partner institutions, and research groups • Carry out some related teaching and other works for the Department that takes into account their career aspirations and development aims _________________________________________________________________________ Selection criteria • Hold or is close to completion of a relevant PhD, together with relevant experience, in the area of probability or statistical machine learning • Possess sufficient specialist knowledge in probability theory and statistical machine learning • Ability to manage own academic research and associated activities • Previous experience of contributing to publications/presentations • Ability to contribute ideas for new research projects and research income generation • Excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings • A commitment to promoting equality, diversity and inclusion Desirable Desirable selection criteria • Specialist knowledge on Stein’s method, or network analysis, or computational biology • Experience of independently managing a discrete area of a research project • Experience of actively collaborating in the development of research articles for publication Pre-employment screening Standard checks If you are offered the post, the offer will be subject to standard pre-employment checks. You will be asked to provide: proof of your right-to-work in the UK; proof of your identity; and (if we haven’t done so already) we will contact the referees you have nominated. You will also be asked to complete a health declaration so that you can tell us about any health conditions or disabilities for which you may need us to make appropriate adjustments. Please read the candidate notes on the University’s pre-employment screening procedures at: https://www.jobs.ox.ac.uk/pre-employment-checks _________________________________________________________________________ About the University of Oxford Welcome to the University of Oxford. We aim to lead the world in research and education for the benefit of society both in the UK and globally. Oxford’s researchers engage with academic, commercial and cultural partners across the world to stimulate high-quality research and enable innovation through a broad range of social, policy and economic impacts. We believe our strengths lie both in empowering individuals and teams to address fundamental questions of global significance, while providing all our staff with a welcoming and inclusive workplace that enables everyone to develop and do their best work. Recognising that diversity is our strength, vital for innovation and creativity, we aspire to build a truly diverse community which values and respects every individual’s unique contribution. While we have long traditions of scholarship, we are also forward-looking, creative and cutting-edge. Oxford is one of Europe's most entrepreneurial universities and we rank first in the UK for university spin-outs, and in recent years we have spun out 15-20 new companies every year. We are also recognised as leaders in support for social enterprise. Join us and you will find a unique, democratic and international community, a great range of staff benefits and access to a vibrant array of cultural activities in the beautiful city of Oxford. For more information, please visit www.ox.ac.uk/about/organisation. The Department of Statistics The Department of Statistics at Oxford is a world-leading centre for research with a broad portfolio that covers pure theory, the development of innovative methods to analyse and understand data, and their applications to scientific and societal problems. Research is loosely structured around seven interconnected research groups: Statistical Theory and Methodology; Computational Statistics and Machine Learning; the Oxford Protein Informatics Group; Probability; Statistical Genetics and Epidemiology; Econometrics and Population Statistics; and Computational Biology and Bioinformatics. The Department has recently undergone a period of rapid expansion, growing from 21 submitted researchers in the 2014 Research Excellence Framework exercise to 32 in REF 2021. The Department relocated to a newly renovated building on St Giles’ in the heart of the University of Oxford in 2015. The building provides state-of-the-art teaching facilities and modern space to facilitate collaboration and integration, creating a highly visible centre for Statistics in Oxford. Since moving to St Giles’, Faculty have secured over £14m in research funding from a variety of funders including UKRI, the Wellcome Trust, the European Commission, NIH, and industrial partners from sectors ranging from services to pharma. Research from the Department of Statistics and the Mathematical Institute in Oxford was submitted together for the UK’s most recent national research assessment exercise, the Research Excellence Framework (REF) 2021. Overall, 78% of our submission was judged to be 4* (the _________________________________________________________________________ highest score available, for research quality that is world-leading in terms of originality, significance, and rigour). This outstanding result is a testament to the breadth, quality and impact of the research produced by colleagues in our two departments, and the outstanding environment in which they work, supported by our excellent professional services staff. The Department’s research excellence has been recognised both collectively, through success in REF 2021, and individually. Alison Etheridge was appointed Dame Commander of the Order of the British Empire in the 2025 New Years Honours. Awards include Fellowships of the Royal Society to Christl Donnelly and Alison Etheridge; Fellowship of the British Academy to Frank Windmeijer; FMedSci and the Zoological Society of London’s Frink Award to Christl Donnelly; the Royal Statistical Society Guy Medal in Bronze to Chris Holmes; the Weldon Memorial Prize, the Francis Crick Prize Lecture, and the Genetics Society Balfour Prize to Simon Myers. Alison Etheridge, Christina Goldschmidt and Gesine Reinert are all Fellows of the Institute of Mathematical Statistics, and Alison Etheridge is a former President. Alison Etheridge was also elected as a member of the American Academy of Arts and Sciences. The Department is home to Oxford University Statistical Consulting, which provides comprehensive statistical consultancy services to both internal departments and external businesses. It operates across a wide range of sectors, and offers experience in all aspects of data-based research. The service includes two Research Software Engineers who take new and existing software platforms from the Oxford Protein Informatics Group, and provide support to industry to maximise their impact. The Department of Statistics offers an undergraduate degree (BA or MMath) in Mathematics and Statistics and an MSc in Mathematical Science (OMMS), both joint with the Mathematical Institute, and an MSc in Statistical Science, as well as a lively and stimulating environment for postgraduate researchers (DPhil or MSc by Research). The Department is involved in five Centres for Doctoral Training (CDTs): the EPSRC CDT in Modern Statistics and Statistical Machine Learning (led by Imperial), the EPSRC CDT in Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research, the EPSRC CDT in Mathematics of Random Systems (with the Mathematical Institute and Imperial), the EPSRC CDT in Health Data Science (with the Big Data Institute) and the recently launched Fundamentals of AI CDT which is funded by the Ellison Institute of Technology. The Department is also part of the National Academy for PhD Training in Statistics, which provides training in fundamental areas of Statistics and Applied Probability. Our graduate students go on to varied careers, the most popular being academia (45%) and the technology (nearly 30%) and finance sectors. The Department maintains well-established connections with interdisciplinary centres such as the Wellcome Centre for Human Genetics and the Big Data Institute. Many Faculty have associations with the Alan Turing Institute (the Turing), the UK’s national centre for data science, in which Oxford is a founding partner. The Department also enjoys close links with the Ellison Institute of Technology, a newly established company which combines cutting-edge research and commercial capability, to drive scientific breakthroughs through creating sustainable companies. Chris Holmes, Professor of Biostatistics, is the _________________________________________________________________________ Director of AI for EIT, and Gil McVean, Principal Scientist for the Pathogen Progamme, also has a joint appointment with the Department of Statistics as Professor of Statistical Genetics. The Department of Statistics holds a silver Athena Swan award to recognise advancement of gender equality: representation, progression and success for all. For more information please visit: www.stats.ox.ac.uk. The Mathematical, Physical and Life Sciences Division The Mathematical, Physical, and Life Sciences (MPLS) Division is one of the four academic divisions of the University. Oxford is widely recognised as one of the world's leading science universities. The disciplines within the MPLS Division regularly appear at the highest levels in world rankings and the REF 2021 results highlighted the quality of its research, the environment in which it is conducted, and the impact it has. The MPLS Division is home to the non-medical sciences at Oxford and its 9 academic departments span the full spectrum of the mathematical, computational, physical, engineering and life sciences, and undertake both fundamental research and cutting-edge applied work. Research in MPLS tackles major societal and technological challenges – whether developing new energy solutions or improved cancer treatments, understanding climate change processes, or helping to preserve biodiversity, and is increasingly focused on key interdisciplinary issues. MPLS Division also includes Begbroke Science Park – the only science park wholly owned and managed by Oxford University. It stands at the forefront of innovative collaboration; a place where science and industry meet. We collaborate closely with colleagues in Oxford across the medical sciences, social sciences and humanities, and with other universities, research organisations and industrial partners across the globe in pursuit of innovative research geared to address critical and fundamental scientific questions. The disciplines within the MPLS Division appear at the highest levels in world rankings, with Oxford’s mathematical, physical and life sciences research regularly identified as one of the most significant recipients of grant funding in Europe. MPLS is proud to be the home of some of the most creative and innovative scientific thinkers and leaders working in academe. Our senior researchers have been awarded some of the most significant scientific honours, including the most recent award of a Nobel Prize for Physics 2020 to Sir Roger Penrose. Within MPLS we are as focused on the next generation as we are on those who have gone before, having a strong tradition of attracting and nurturing the very best early career researchers who regularly secure prestigious fellowships and faculty positions. MPLS continues in its work to support diversity in its staffing, seeing that it will bring benefits to everyone. All academic departments in the Division hold Athena Swan Awards (The Athena Swan _________________________________________________________________________ Charter encourages and recognises commitment to advancing the careers of women in science, technology, engineering, maths and medicine employment in higher education and research.) We have around 7,400 full and part-time students (including approximately 3,500 graduate students) and play a major role in training the next generation of leading scientists. Oxford's international reputation for excellence in teaching is reflected in its position at the top of the major league tables and subject assessments. MPLS academics educate students of high academic merit and potential from all over the world. Through a mixture of lectures, practical work and the distinctive college tutorial system, students develop their ability to solve major mathematical, scientific and engineering problems. MPLS is dedicated to bringing the wonder and potential of science to the attention of audiences far beyond the world of academia. We have a strong commitment to supporting public engagement in science through initiatives including the Oxford Sparks portal and Science Together programme. These are complemented by a large variety of outreach activities; these are crucial activities given so many societal and technological issues demand an understanding of the science that underpins them. We also bring the potential of our scientific efforts forward for practical and beneficial application to the real world and our desire, aided by the work of Oxford University Innovation and Oxford Science Enterprises, is to link our best scientific minds with industry and public policy makers. For more information about the MPLS division, please visit: www.mpls.ox.ac.uk How to apply Applications are made through our online recruitment portal. Information about how to apply is available on our Jobs website https://www.jobs.ox.ac.uk/how-to-apply. Your application will be judged solely on the basis of how you demonstrate that you meet the selection criteria stated in the job description. Applicants should ask their referees to send their letters of reference directly to the HR Administrator by email to hr@stats.ox.ac.uk by the closing date quoting the vacancy reference number. You will be asked to upload a CV and a supporting statement. The supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants) Please upload all documents as PDF files with your name and the document type in the filename e.g., SMITH_CV. All applications must be received by midday UK time on the closing date stated in the online advertisement. _________________________________________________________________________ Information for priority candidates A priority candidate is a University employee who is seeking redeployment because they have been advised that they are at risk of redundancy, or on grounds of ill-health/disability. Priority candidates are issued with a redeployment letter by their employing department(s). If you are a priority candidate, please ensure that you attach your redeployment letter to your application (or email it to the contact address on the advert if the application form used for the vacancy does not allow attachments). If you need help Application FAQs, including technical troubleshooting advice is available at: https://staff.web.ox.ac.uk/recruitment-support-faqs Non-technical questions about this job should be addressed to the recruiting department directly (hr@stats.ox.ac.uk). To return to the online application at any stage, please go to: www.recruit.ox.ac.uk. Please note that you will receive an automated email from our online recruitment portal to confirm receipt of your application. Please check your spam/junk mail if you do not receive this email. Important information for candidates Data Privacy Please note that any personal data submitted to the University as part of the job application process will be processed in accordance with the GDPR and related UK data protection legislation. For further information, please see the University’s Privacy Notice for Job Applicants at: https://compliance.admin.ox.ac.uk/job-applicant-privacy-policy. The University’s Policy on Data Protection is available at: https://compliance.admin.ox.ac.uk/data-protection-policy. The University’s policy on retirement The University operates an Employer Justified Retirement Age (EJRA) for very senior research posts at grade RSIV/D35 and clinical equivalents E62 and E82, which with effect from 1 October 2023 will be 30 September before the 70th birthday. The justification for this is explained at: https://hr.admin.ox.ac.uk/the-ejra. For existing employees on these grades, any employment beyond the retirement age is subject to approval through the procedures: https://hr.admin.ox.ac.uk/the-ejra. There is no normal or fixed age at which staff in posts at other grades have to retire. Staff at these grades may elect to retire in accordance with the rules of the applicable pension scheme, as may be amended from time to time. _________________________________________________________________________ Equality of opportunity Entry into employment with the University and progression within employment will be determined only by personal merit and the application of criteria which are related to the duties of each particular post and the relevant salary structure. In all cases, ability to perform the job will be the primary consideration. No applicant or member of staff shall be discriminated against because of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. _________________________________________________________________________ Benefits of working at the University Employee benefits University employees enjoy 38 days’ paid holiday, generous pension schemes, travel discounts, and a variety of professional development opportunities. Our range of other employee benefits and discounts also includes free entry to the Botanic Gardens and University colleges, and discounts at University museums. See https://hr.admin.ox.ac.uk/staff-benefits University Club and sports facilities Membership of the University Club is free for all University staff. The University Club offers social, sporting, and hospitality facilities. Staff can also use the University Sports Centre on Iffley Road at discounted rates, including a fitness centre, powerlifting room, and swimming pool. See www.club.ox.ac.uk and https://www.sport.ox.ac.uk/. Information for staff new to Oxford If you are relocating to Oxfordshire from overseas or elsewhere in the UK, the University's Welcome Service website includes practical information about settling in the area, including advice on relocation, accommodation, and local schools. See https://welcome.ox.ac.uk/ There is also a visa loan scheme to cover the costs of UK visa applications for staff and their dependants. See https://staffimmigration.admin.ox.ac.uk/visa-loan-scheme Family-friendly benefits With one of the most generous family leave schemes in the Higher Education sector, and a range of flexible working options, Oxford aims to be a family-friendly employer. We also subscribe to the Work+Family Space, a service that provides practical advice and support for employees who have caring responsibilities. The service offers a free telephone advice line, and the ability to book emergency backup care for children, adult dependents and elderly relatives. See https://hr.admin.ox.ac.uk/my-familycare Childcare The University has excellent childcare services, including five University nurseries as well as Universitysupported places at many other private nurseries. For full details, including how to apply and the costs, see https://childcare.admin.ox.ac.uk/ Disabled staff We are committed to supporting members of staff with disabilities or long-term health conditions. For further details, including information about how to make contact, in confidence, with the University’s Staff Disability Advisor, see https://edu.admin.ox.ac.uk/disability-support _________________________________________________________________________ Staff networks The University has a number of staff networks including the Oxford Research Staff Society, BME staff network, LGBT+ staff network and a disabled staff network. You can find more information at https://edu.admin.ox.ac.uk/networks The University of Oxford Newcomers' Club The University of Oxford Newcomers' Club is an organisation run by volunteers that aims to assist the partners of new staff settle into Oxford, and provides them with an opportunity to meet people and make connections in the local area. See www.newcomers.ox.ac.uk.
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179779 - (Senior) Statistical Consultant Job Description
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