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This is a re-advertisement, previous applicants need not apply We invite applications for the position of a Postdoctoral Researcher in Artificial Intelligence to join the research group of Professor Christopher Yau (http://cwcyau.github.io) based in the Big Data Institute at the University of Oxford. The position is embedded within a research programme funded as part of a UKRI Turing AI Fellowship (https://www.ukri.org/news/new-turing-ai-fellows-to-deliver-world-class-ai-research/). The role will focus on the development of state-of-the-art machine learning approaches to produce AI-driven tools for the analysis of multimodal molecular and clinical data as part of several collaborations with industry and academia. Special areas of interest include the development of foundation models using electronic health records and multi-omics data integration for cancer and vaccines research. A significant measure of success of this Fellowship will be the future career destinations of its team members. The Principal Investigator is therefore highly invested in positively supporting the career development of research team members. You will therefore take a lead role in shaping our engagement with collaborators and be passionate about actively engaging with the public and patients to build a comprehensive personal profile to enhance future employability. This is a significant opportunity for an individual to develop a balanced long-term independent research career in artificial intelligence for health. You will have a PhD in a quantitative subject (e.g. mathematics, physics, computer science, engineering) and possess experience of developing computational models. Applications from researchers looking to switch disciplines into probabilistic machine learning are welcome. A strong interest in biology and medicine is essential. You should be self-motivated, diligent, and able to work individually or collaboratively. For an informal discussion about the post, please contact Dr Christopher Yau (christopher.yau@wrh.ox.ac.uk). This position is full-time and fixed-term for 24 months. This post is available from January 2024. Applications for flexible working arrangements are welcomed and will be considered in line with business needs. You will be required to upload a CV and Supporting Statement as part of your online application. Click here for information and advice on writing an effective Supporting Statement: https://www.jobs.ox.ac.uk/cv-and-supporting-statement. The closing date for applications is 12.00 noon on 6th November 2023.
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Nuffield Department of Women's and Reproductive Health
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Nuffield Department for Women’s & Reproductive Health, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus.
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John Radcliffe Hospital Women's Centre, Headley Way
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**This is a re-advertisement, previous applicants need not apply** We invite applications for the position of a Postdoctoral Researcher in Artificial Intelligence to join the research group of Professor Christopher Yau (http://cwcyau.github.io) based in the Big Data Institute at the University of Oxford. The position is embedded within a research programme funded as part of a UKRI Turing AI Fellowship (https://www.ukri.org/news/new-turing-ai-fellows-to- deliver-world-class-ai-research/). The role will focus on the development of state-of-the-art machine learning approaches to produce AI-driven tools for the analysis of multimodal molecular and clinical data as part of several collaborations with industry and academia. Special areas of interest include the development of foundation models using electronic health records and multi-omics data integration for cancer and vaccines research. A significant measure of success of this Fellowship will be the future career destinations of its team members. The Principal Investigator is therefore highly invested in positively supporting the career development of research team members. You will therefore take a lead role in shaping our engagement with collaborators and be passionate about actively engaging with the public and patients to build a comprehensive personal profile to enhance future employability. This is a significant opportunity for an individual to develop a balanced long-term independent research career in artificial intelligence for health. You will have a PhD in a quantitative subject (e.g. mathematics, physics, computer science, engineering) and possess experience of developing computational models. Applications from researchers looking to switch disciplines into probabilistic machine learning are welcome. A strong interest in biology and medicine is essential. You should be self-motivated, diligent, and able to work individually or collaboratively. For an informal discussion about the post, please contact Dr Christopher Yau (christopher.yau@wrh.ox.ac.uk). This position is full-time and fixed-term for 24 months. This post is available from January 2024. Applications for flexible working arrangements are welcomed and will be considered in line with business needs. You will be required to upload a CV and Supporting Statement as part of your online application. Click here for information and advice on writing an effective Supporting Statement: https://www.jobs.ox.ac.uk/cv-and-supporting- statement. The closing date for applications is 12.00 noon on 6th November 2023.
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Grade 7: (£36,024- £44,263) p.a. (with a discretionary range up to £48,350) per annum
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Postdoctoral Researcher in Artificial Intelligence
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Nuffield Department of Obstetrics and Gynaecology
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Job description and selection criteria Job title Postdoctoral Researcher in Artificial Intelligence Department Nuffield Department for Women’s & Reproductive Health Location Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus Grade and salary Grade 7: (£36,024- £44,263) p.a. (with a discretionary range up to £48,350) per annum Hours Full-time (applications for flexible working arrangements are welcomed and will be considered in line with business needs) Contract Type Fixed-term for 24 months with the possibility to extend to 36 months. The post is available from 1st January 2023 Reporting to Dr Christopher Yau Vacancy reference 168531 The Post Overview of the Role We invite applications for the position of a Postdoctoral Researcher in Artificial Intelligence to join the research group of Professor Christopher Yau (http://cwcyau.github.io) which is based within the Big Data Institute at the University of Oxford. The position is embedded within a research programme funded as part of a UKRI Turing AI Fellowship (https://www.ukri.org/news/new-turing-ai-fellows-to-deliver-world-class-ai-research/). The role will focus on the development of state-of-the-art machine learning approaches to produce AI-driven tools for the analysis of multimodal molecular and clinical data as part of a number of collaborations with industry and academia. This is a unique translational science opportunity to develop and apply AI to tackle key questions in medicine. Special areas of interest include the development of foundation models using electronic health records and multi-omics data integration for cancer and vaccines research. A significant measure of success of this Fellowship will be the future career destinations of its team members. The Principal Investigator is therefore highly invested in positively supporting the career development of research team members. You will therefore take a lead role in shaping our engagement with collaborators and be passionate about actively engaging with the public and patients in order to build a comprehensive personal profile to enhance future employability. You will have a PhD in a quantitative subject (e.g. mathematics, physics, computer science, engineering) and possess experience of developing computational models. Applications from researchers looking to switch disciplines into probabilistic machine learning are welcome. A strong interest in biology or medicine is essential. You should be self-motivated, diligent and able to work individually or collaboratively. Responsibilities • Develop state-of-the-art probabilistic modelling and/or machine learning methods. • Work closely with clinical partners to develop novel opportunities for embedding artificial intelligence in clinical care. • Produce well-documented open source code implementing algorithms for general use adhering to established frameworks for best practice in research software engineering. • Understand and apply rigorous standards of open and transparent reporting in production of scientific publications. • To be able to present confidently their research outcomes to a range of stakeholder groups, including public and patient groups, in a number of settings including national and international conferences. 2 • Learn and implement best practice for collaboratively effectively with internal staff and external stakeholders in achieving research goals and understand the importance of embedding equality, diversity and inclusion issues in our work. • Work closely with the Principal Investigator to develop and eventually apply project management skills in the implementation of this project • Develop and eventually apply person management skills to supervise other staff or research students Selection criteria Applications will be judged only against the criteria that are set out below. Applicants should ensure that their application shows very clearly how their skills and experience meet these criteria. Essential: 1. Undergraduate or Masters degree (or equivalent) with a significant mathematical or a. computational element, e.g. in Mathematics, Computer Science, Engineering, Physics or Statistics 2. Doctorate (or equivalent) with a significant computational and/or statistical element 3. Significant experience of probabilistic modelling and/or machine learning 4. Significant experience of scientific programming 5. Strong interest in medicine and biology 6. Strong scientific publication record relative to career stage 7. Motivated to engage with the public and patients in their research 8. Self-motivated, diligent and able to work in a team 9. Excellent organisational and communication skills 10. Fluent communicator in written and spoken English Desirable: Please note that the criteria listed below would be an advantage in this role, but you do not need to meet them to be eligible to apply. 1. Strong knowledge and understanding of Bayesian statistical modelling 2. Experience of approaches for causal inference 3. Knowledge of state-of-the-art machine learning approaches, particularly using Deep Neural Networks, such as variational autoencoders, amortised learning, normalising flows, etc. 4. Experience of writing probabilistic modelling software in R or Python. 3 5. Experience of implementing software using Deep Learning frameworks (e.g. Tensorflow, PyTorch) 6. Experience of using a High Performance Computing (HPC) environment. 7. Experience of best practice for modern software development (e.g using version control, i.e. GitHub, snakemake, etc) Pre-employment screening All offers of employment are made subject to standard pre-employment screening, as applicable to the post. If you are offered the post, you will be asked to provide proof of your right-to-work, your identity, and 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 so that we can discuss appropriate adjustments with you), and a declaration of any unspent criminal convictions. We advise all applicants to read the candidate notes on the University’s pre-employment screening procedures, found at: www.ox.ac.uk/about/jobs/preemploymentscreening/. 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 note that if you do not upload a supporting statement, we will be unable to consider your application. 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. 4 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 Help and support is available from: https://hrsystems.admin.ox.ac.uk/recruitment-support If you require any further assistance please email recruitment.support@admin.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 e-recruitment system 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 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: https://hr.admin.ox.ac.uk/the-ejra For existing employees, 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 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. 5 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 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. Nuffield Department of Women’s & Reproductive Health (NDWRH) The Nuffield Department of Women’s & Reproductive Health (NDWRH) is one of the largest and most successful academic departments in the world in its field. There are approximately 160 people working in the department, including senior academic staff, research support staff, clerical and technical staff, and graduate students (including clinicians) carrying out research towards a higher degree. There are also a number of visiting researchers from many parts of the world. The average annual income is approximately £10 million, of which over 75% comes from outside sources. NDWRH encompasses multi-disciplinary research across the full spectrum of women’s health. Our work has four overarching themes; Cancer, Global Health, Maternal & Fetal Health and Reproductive Medicine & Genetics. We focus on genetic studies, the dissection of molecular, biochemical and cellular mechanisms underlying normal and aberrant reproductive tissue function, and clinical studies in women’s health, assisted reproduction and pregnancy, as well as growth and development across the first 1000 days of life. The clinical and laboratory programmes are based in the Women’s Centre, John Radcliffe Hospital; Weatherall Institute of Molecular Medicine; Winchester House, and the Big Data Institute, and there are collaborations with the School’s Institutes, the University’s Science Departments and with researchers outside Oxford, in both the UK and abroad, especially in lowmiddle income countries. For more information please visit: www.wrh.ox.ac.uk The University of Oxford is a member of the Athena SWAN Charter and holds an institutional Bronze Athena SWAN award. NDWRH holds a departmental Silver Athena award in recognition of its efforts to introduce organisational and cultural practices that promote gender equality in SET and create a better working environment for both men and women. 6 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 dependents. 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 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 https://hr.admin.ox.ac.uk/my-family-care 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 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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