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Named in honour of Alan Turing, the Institute is a place for inspiring, exciting work and we need passionate, sharp, and innovative people who want to use their skills to contribute to our mission to make great leaps in data science and AI research to change the world for the better.

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Position:

The Health and Medical Sciences Programme at Turing delivers research into the theory and methods of AI, statistics, and data analytics underpinning medical and health applications that will enable scientists to do better science, without compromising respect for privacy and patient trust.

Hoffman La-Roche (Roche) as a company has been committed to improving lives since it was founded in 1896 in Basel, Switzerland. Today, Roche creates innovative medicines and diagnostic tests that help millions of patients globally and was one of the first companies to bring targeted treatments to patients.

The Alan Turing Institute and Roche have recently launched a new programme which will establish a world-leading industry and academic partnership in advanced analytics focused on enabling the transformative benefits of personalized healthcare to become a reality for patients around the world. This strategic partnership will cover multiple activities, with the “North Star” of developing new data science methods to investigate large, complex, clinical and healthcare datasets to better understand how and why patients respond differently to treatment, and how treatment can be improved. Understanding such “treatment heterogeneity” is a problem at the forefront of modern medicine and is an essential first step toward the ambitious goal of developing a personalised healthcare. Through the partnership, multiple avenues of research on heterogeneity in patient health data will be explored.

To develop this project, the post holder will benefit from being part of multiple communities of researchers, including not only the Alan Turing Institute and Roche but also the Department of Statistical Science at UCL, and the Centre for Health Informatics at the University of Manchester. UCL Statistical Science is the longest established university statistics department in the world and is one of nine departments in the UCL Faculty of Mathematical and Physical Sciences (MAPS). The department has close links with the medical school through the UCLH/UCL NIHR Biomedical Research Centre (BRC) and the UCL Primary Care and Mental Health (PRIMENT) Clinical Trials Unit. The Centre for Health Informatics is a world-leading digital health centre that unites and provides data-intensive research and education across Northern England and beyond.

ROLE PURPOSE

The post is an exciting opportunity for a researcher with a strong background in statistical methodology and applied data analysis, who would like to grow that skill set further by developing novel methodology to evaluate and improve fairness in clinical prediction models. The postholder will work at the Alan Turing Institute on a project funded by the Turing-Roche strategic partnership, as part of a diverse team of experts across UCL and the University of Manchester, including Dr Brieuc Lehmann (PI, UCL), Dr Matthew Sperrin (Manchester), Dr Karla Diaz-Ordaz (UCL) and Dr Ricardo Silva (UCL).

Clinical prediction models (CPMs) take known information (‘predictors’) about patients, and use statistical modelling or machine learning to predict outcomes. These predictions are typically used to inform clinical decisions. While CPMs can improve clinical decision-making, there are growing concerns that CPMs could perpetuate or even exacerbate health inequalities. CPMs are trained on historical biomedical data, so the outcomes observed in the training data reflect historical treatment, monitoring and triaging decisions. Therefore, any bias and unfairness in the current system is reflected in the predictions and the predictor-outcome relationships that the algorithms generate. Moreover, existing biomedical datasets may not be representative of the target population on which CPMs are deployed. As a result, predictive performance for underrepresented groups may suffer, leading to poorer decision-making.

The postholder will explore statistical and machine learning methods to measure and minimise biases and unfairness in CPMs. Specifically, the candidate will use tools from causality and data augmentation to estimate and evaluate counterfactual fairness, and develop novel value-of-information methods to estimate the benefit to fairness in collecting more data from underrepresented groups. The application of focus will be lung cancer, which disproportionately affects those in more deprived areas and ethnic minority groups, who are typically diagnosed with later stage disease. The postholder will gain valuable experience working with complex biomedical datasets, by applying these methods to studies including the Manchester Lung Health Check Programme and UK Biobank.

This is a stand-out opportunity to work within a number of world-leading institutions, and which will give postholder visibility of many facets of the pharmaceutical industry and support to develop a network of contacts in both academia and industry. The position will provide a valuable opportunity for the postholder to develop their methodological and applied research portfolio and expertise on the impactful topic of fairness in healthcare.

This role is open for applicants at either a junior or senior level, and the final offer will be made based on the applicant’s overall skills and level of experience.

DUTIES AND AREAS OF RESPONSIBILITY

• Undertake work including statistical analyses and relevant methodological research.
• Publish the results of the methodological and applied research in high-quality journals and participate in national and international conferences.
• Communicate technical topics and research outputs to colleagues and external partners by preparing presentations and reports and and taking an active role in meetings and discussions. Work collaboratively with members of the Turing-Roche partnership team, the Roche Advanced Analytics group and other colleagues at Turing, UCL and Manchester University.
• Maintain up to date skills and knowledge of statistical methods that are of relevance to the area of investigation.
• Develop and test methods to measure and minimise biases and unfairness in CPMs, including:

i) data augmentation tools to assess counterfactual fairness with respect to protected characteristics

ii) doubly-robust methods to estimate counterfactual fairness with respect to the treatment decision

iii) value-of-information methods to inform targeted data collection for more representative training datasets

• Maintain effective communication and accurate records.
• Maintain own continuing professional development
• Actively follow and promote Turing/UCL policies, including those relating to Equality, Diversity and Inclusivity.

If appointed at a Senior Research Associate level, the post-holder will have additional responsibilities, such as:

• To define the research direction in collaboration with the PIs of the project.
• To take the lead on writing up research findings as they emerge, producing reports, and developing publications in peer reviewed journals, in collaboration with the research team.
• Extend, transform and apply knowledge acquired from scholarship to research and appropriate external activities
• Assist and then lead in the preparation of proposals and applications to external bodies, e.g. for funding and contractual purposes;
• Support externally funded research projects; identify and work with senior colleagues to develop research ideas and contribute to funding proposals.
• Contribute to the supervision of postgraduate students, including PhD students, and mentor junior colleagues

Requirements:

• A PhD (awarded or waiting for viva) or equivalent experience/qualifications in a relevant area such as Mathematics, Statistics, Computer Science, or related discipline
• Knowledge of a wide range of statistical and/or machine learning methods used for prediction
• Excellent computational skills with a statistical software programming language (e.g. R, python, Julia)
• Excellent written and/or verbal communication skills including the ability to present complex or technical information, and to communicate effectively with analysts and other stakeholders outside the research community
• Excellent teamwork skills and ability to collaborate successfully with colleagues in a multidisciplinary environment
• Ability to represent the partnership at events and high-level meetings
• Ability to use own judgement to analyse and solve problems
• Ability to consider possible solutions and identify with evidence those which offer widest benefits.

Other information:

APPLICATION PROCEDURE

If you are interested in this opportunity, please click the apply button below. You will need to register on the applicant portal and complete the application form including your CV and covering letter. If you have questions about the role or would like to apply using a different format, please contact us on 020 3862 3533 or 0203 862 3516, or email [email protected].

If you are applying for more than one role at the Turing, please note that only one Cover Letter can be visible on your profile at one time. If you wish to apply for multiple roles and do not want to overwrite your existing Cover Letter, please apply for the role using the button below and forward your additional cover letter directly to [email protected] quoting the job title.

We are currently assessing the results of our hybrid working trial, which ran for six months. We will soon publish a long-term workplace policy: as a guide, we anticipate this will be between 2-4 days per month. Some roles may require the jobholder to spend a greater number of days in the office, but the hiring manager will be able to confirm this during the interview

CLOSING DATE FOR APPLICATIONS: 21 March 2023 at 23:59

We reserve the right to close this vacancy early if enough applications are received.

TERMS AND CONDITIONS

This full time post is offered on a fixed term basis for 18 months starting as soon as possible. If appointed as research associate, the annual salary range would be £40,850- £46,200 depending on experience. If appointed as senior research associate, the annual salary range would be £51,025- £52,500 depending on experience. These will include flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits

EQUALITY, DIVERSITY, AND INCLUSION

The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy and maternity, religion or belief, sex and sexual orientation.

We are committed to building a diverse community and would like our leadership team to reflect this. We therefore welcome applications from the broadest spectrum of backgrounds.

We are committed to making sure our recruitment process is accessible and inclusive. This includes making reasonable adjustments for candidates who have a disability or long-term condition. Please contact us at [email protected] to find out how we can assist you.

Please note all offers of employment are subject to obtaining and retaining the right to work in the UK and satisfactory pre-employment security screening which includes a DBS Check.

Full details on the pre-employment screening process can be requested from [email protected].