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We are seeking four Senior Postdoctoral Researchers to join a new Oxford-GSK partnership focused on biostatistics and artificial intelligence (AI) for application in medicine. Each Senior Postdoctoral Researcher will play a key role in shaping the research within the thematic areas of interest. With a cross-departmental base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will focus on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor Chris Holmes, and with scientific oversight from Oxford Principal Investigators and GSK scientists, the centre will initially focus on some of the following thematic areas: • Decision analysis under model misspecification • Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools; Code synthesis for causality • Generalisability, transportability and validation of multiomics ML across biobanks More details on thematic areas can be found here; https://www.bdi.ox.ac.uk/research/oxford-gsk-collaboration-in-biostatistics-and-artificial-intelligence-in-medicine As a Senior Postdoctoral Researcher, you will be responsible for planning and managing your own research programme within the collaboration. You will work closely with Principal Investigators and industry scientists to agree clear task objectives, organise work and delegate as appropriate, keeping accurate and comprehensive records of work undertaken. You will contribute intellectually to the development of ‘pathfinder’ projects and help shape the direction of research themes and the wider partnership in the longer term for delivery of new methods relevant for drug discovery analysis pipelines, trial design and operational efficiency. Other responsibilities will include helping with supervision of PhD students working on projects as part of the initiative, performing analysis in close contact with the associated clinical researchers and taking responsibility for completion of data analyses. You will communicate on a regular basis with the relevant theme leads (Oxford and GSK) and wider team on all issues relating to the development and application of new methods, ensuring they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification research experience. You will have experience in and an ability to develop research projects, with a strong publication record in peer-reviewed journals and conferences. You will have a proven ability in providing intellectual support and technical advice on projects and in assisting others in tools relating to data processing and analysis. A forward-thinking, collaborative approach to research will be essential to meet the aims of the partnership. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must specify which thematic areas you are interested in working on, and explain how you meet each of the selection criteria for the post using examples of your skills and experience. This position is offered full time on a fixed term contract until 30 September 2028 and is funded by GSK. Only applications received before 12 midday on 19 May 2025 will be considered. Please quote 177230 on all correspondence.
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Job title Senior Postdoctoral Researcher in application of AI for medicine Division Medical Sciences Department Nuffield Department of Medicine Location Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford, OX3 7LF Grade and salary Research Grade 8: Salary in range £48,235 - £51,059 per annum (pro rata). This is inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata). Hours Full time Contract type Fixed-term contract for 36 months Funding is provided by GSK Reporting to Professor Chris Holmes, Principle Investigator, and Partnership Theme Lead Vacancy reference 177230 Additional information This role meets the eligibility requirements for a Skilled Worker Certificate of Sponsorship under UK Visas and Immigration legislation. About us • • • What we offer https://hr.admin.ox.ac.uk/staff-benefits • An excellent contributory pension scheme • 38 days annual leave • A pensionable Oxford University Weighting allowance of £1,500 per annum (pro rata) • A comprehensive range of childcare services • Family leave schemes • Cycle loan scheme • Discounted bus travel and Season Ticket travel loans • Membership to a variety of social and sports clubs • A welcoming and diverse community Research topic AI and biostatistics with application to medicine Principal Investigator / supervisor Professor Chris Homes & Partnership Theme Lead Project team Oxford-GSK Centre for Biostatistics & AI in Medicine Funding partner The funds supporting this research project are provided by GSK University of Oxford - www.ox.ac.uk/about/organisation Nuffield Department of Medicine (NDM) - https://www.ndm.ox.ac.uk Unit - https://www.bdi.ox.ac.uk/ The role We are seeking four Senior Postdoctoral Researchers to join a new Oxford-GSK partnership focused on biostatistics and artificial intellegence (AI ) for application in medicine, each of whom will play a key role in shaping the research within thematic areas of interest. You will bring experience in a quantitative or computer science-related subject, with experience at the post-doctoral level, and a drive to work across a range of themes with research experts in a number of specialisms. Training will be provided for successful applicants across a variety of scientific disciplines, as required. Whilst you will be a member of the Nuffield Department of Medicine with a base in the Big Data Institute, the partnership offers an opportunity to work with leading Principal Investigators from Departments in other parts of the University, including Engineering Sciences, Computer Sciences, Statistics and Saïd Business School. This role is relevant both for candidates with a strong background in machine learning and seeking to branch out into healthcare, or with strengths in biostatistics and keen to develop in the area of machine learning. The Project The University of Oxford and GSK have recently formed a new partnership focused on biostatistics and artificial intelligence (AI) for application in medicine. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists, forming small teams focused on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor Chris Holmes, with scientific oversight from Oxford Principal Investigators and GSK scientists, the centre will initially focus on the following thematic areas: • • • • • • Decision analysis under model misspecification Uncertainty quantification around LLMs Constrained experimental design Combining models and combining data / Realistic simulation of clinical trials Developing LLMs to utilise ODEs and ProbML as tools, Code synthesis for causality Generalisability, transportabilty and validation of multiomics ML across biobanks Please see https://www.bdi.ox.ac.uk/research/oxford-gsk-collaboration-in-biostatistics-and-artificialintelligence-in-medicine for further information on the thematic areas. Principal Investigators from Oxford for this programme are Professor David Clifton (Department of Engineering Science), Professor Robin Evans (Department of Statistics), Associate Professor Yarin Gal (Department of Computer Science), Associate Professor Agni Orfanoudaki (Saïd Business School) in and Associate Professor Tom Rainforth (Department of Statistics). Teams will have a base in the University of Oxford’s Big Data Institute and will be well supported by a dedicated data scientist, as well as a programme manager. 1 Responsibilities You will: • • • • • • • • • • • • Plan and manage own research programme within the collaboration. Work closely with senior academic researchers and industry scientists, to agree clear task objectives, organise work and delegate as appropriate, keeping accurate and comprehensive records of work undertaken. Contribute intellectually to the development of ‘pathfinder’ projects and help shape the direction of research themes and wider partnership in the longer term for delivery of new methods relevant for drug discovery analysis pipelines, trial design and operational efficiency. Willingness to work flexibly across thematic areas and projects where there is opportunity for added value and conceptual advancement, coaching other members of the group on specialist methodologies or analytical approaches. Write research articles at a national level for peer-reviewed journals, book chapters, and reviews. Present papers at national conferences, and lead seminars to disseminate research. Perform the analysis in close contact with the associated clinical researchers and to take responsibility for completion of data analyses. Communicate on a regular basis with the relevant theme leads (Oxford and GSK) and wider team on all issues relating to the development and application of new methods, ensuring they are kept fully up to date with progress and difficulties in the research projects. Present research project updates to the partnership senior leadership team as required. Work in collaboration with machine learning and statistics groups in the University to exploit existing resources, tools and methods to their full potential, maintaining confidentiality regarding research data when interacting with colleagues outside of the collaboration Assist with the supervision of doctoral students joining the partnership, assist with related teaching and other work for the departments that takes into account career development aims Perform any other comparable duties as may reasonably be required to ensure the efficient running of the collaboration. Participate in and support the public engagement and widening access activities of the Department and the University. This is anticipated to be not more than 2 days per year. Undertake mandatory training as required by the University, Division and Department. The specific list of training courses may change from time-to-time, in response to both legal and internal University requirements. 2 Selection criteria Essential • • • • • • • Hold a PhD/DPhil in a quantitative or computer science related subject (eg Statistics, Machine Learning, Biostatistics, AI, Engineering). Post-qualification research experience. Extensive relevant research experience in a quantitative or computer science related subject and an ability to develop research projects, with a strong publication record in peer-reviewed journals and conferences. Excellent interpersonal, communication and team working skills, with an ability to collaborate effectively with computational, wet-lab and clinical scientists, while taking personal responsibility for assigned tasks. The proven ability to communicate technical advice and provide intellectual support, and assist others in tools relating to data processing and analysis. An approach to research which will directly contribute to, and benefit from, the forward thinking and collaborative ethos of the programme. A willingness and flexibility to work across a broad range of themes with scientists with distinct academic specialisms, and to branch out and develop skills across unfamiliar research areas (as necessary). Desirable • • • • • Experience of conducting complex applied statistical analyses using R packages, Python or other software tools. Experience with model building and algorithm development (which could include using Bayesian methods). Knowledge of modern computational statistics and/or machine learning approaches. Experience in High Performance Computing environments. Experience in managing staff and supervising students. 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 3 How to apply Applications are made through our e-recruitment system and you will find all the information you need about how to apply on our Jobs website https://www.jobs.ox.ac.uk/how-to-apply. If you would like to apply, click on the Apply Now button on the ‘Job Details’ page and follow the onscreen instructions to register as a new user or log-in if you have applied previously. As part of your application you will be asked to provide details of two referees and indicate whether we can contact them now. 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). 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. Please note using a long file name may prevent you from uploading your documents. • http://www.ox.ac.uk/about_the_university/jobs/research/ All applications must be received by midday UK time on the closing date stated in the online advertisement. If you currently work for the University please note that: • • As part of the referencing process, we will contact your current department to confirm basic employment details including reason for leaving. Although employees may hold multiple part-time posts, they may not hold more than the equivalent of a full time post. If you are offered this post, and accepting it would take you over the equivalent of full-time hours, you will be expected to resign from, or reduce hours in, your other posts(s) before starting work in the new post. 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 recruitment@ndm.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 4 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. 5
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Research Grade 8: Research Grade 8: Salary in range £48,235 - £51,059 per annum (pro rata). This is inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata).
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We are seeking four Senior Postdoctoral Researchers to join a new Oxford-GSK partnership focused on biostatistics and artificial intelligence (AI) for application in medicine. Each Senior Postdoctoral Researcher will play a key role in shaping the research within the thematic areas of interest. With a cross-departmental base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will focus on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor Chris Holmes, and with scientific oversight from Oxford Principal Investigators and GSK scientists, the centre will initially focus on some of the following thematic areas: • Decision analysis under model misspecification • Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools; Code synthesis for causality • Generalisability, transportability and validation of multiomics ML across biobanks More details on thematic areas can be found here; https://www.bdi.ox.ac.uk/research/oxford-gsk-collaboration-in-biostatistics- and-artificial-intelligence-in-medicine As a Senior Postdoctoral Researcher, you will be responsible for planning and managing your own research programme within the collaboration. You will work closely with Principal Investigators and industry scientists to agree clear task objectives, organise work and delegate as appropriate, keeping accurate and comprehensive records of work undertaken. You will contribute intellectually to the development of ‘pathfinder’ projects and help shape the direction of research themes and the wider partnership in the longer term for delivery of new methods relevant for drug discovery analysis pipelines, trial design and operational efficiency. Other responsibilities will include helping with supervision of PhD students working on projects as part of the initiative, performing analysis in close contact with the associated clinical researchers and taking responsibility for completion of data analyses. You will communicate on a regular basis with the relevant theme leads (Oxford and GSK) and wider team on all issues relating to the development and application of new methods, ensuring they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification research experience. You will have experience in and an ability to develop research projects, with a strong publication record in peer-reviewed journals and conferences. You will have a proven ability in providing intellectual support and technical advice on projects and in assisting others in tools relating to data processing and analysis. A forward-thinking, collaborative approach to research will be essential to meet the aims of the partnership. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must **specify which thematic areas you are interested in working on** , and **explain how you meet each of the selection criteria** for the post using examples of your skills and experience. This position is offered full time on a fixed term contract until 30 September 2028 and is funded by GSK. Only applications received before 12 midday on 19 May 2025 will be considered. Please quote **177230** on all correspondence.