The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.

We are seeking a full-time post-doctoral Research Associate (RA) to work on the Turing Project “Evaluation of Complex Forensic Evidence”. The researcher will be part of a team of top academics in Bayesian statistics, decision theory and causal inference and be based at The Alan Turing Institute in London. The research team includes: Dr Anjali Mazumder (co-PI), Dr Amy Wilson (co-PI), Professor Jim Smith (Warwick), Professor Philip Dawid (Cambridge), Professor Henry Wynn (LSE), and colleagues across Europe and the US. Researchers will meet regularly with the research team and will engage with forensic science practitioners in industry and government.

Forensic evidence can consist of multiple different types of evidence (e.g. DNA, blood stains, eyewitness) that can be highly correlated (e.g. DNA evidence taken from a blood stain), with each case having unique types and networks of relevant information. There is often limited population and experimental data, so methods for eliciting information from experts and dealing with epistemic uncertainty are required. This project aims to draw upon real cases to determine a framework for the evaluation of complex forensic evidence that deals with the multiple statistical issues and complex data structures that can occur. There is particular interest in understanding activity level propositions, using graphical representations such as Bayesian networks, Wigmore charts and chain event graphs.

The specific goals are:

• Developing a coherent and systematic probabilistic framework for the interpretation of complex criminal cases, that accounts for multiple types of evidence, addresses propositions at different levels, and incorporates expert judgement and multiple sources of uncertainty.
• Developing statistical methods to address the computational complexities of combining different modelling substructures, to model evidence conflict, and to facilitate the modelling of the case circumstances.
• Applying modern approaches to statistical causal reasoning to understand the relevance of the evidence to the legal issues in a case.

Informal enquiries may be made to the PIs ([email protected] and [email protected]).

Duties and Responsibilities

• Perform high quality research in Bayesian statistical modelling, causal inference and its applications as relevant to the project.
• Write and contribute to research publications, documenting results of the research, to publish in relevant peer-reviewed scientific journals of international standing, to present these results at conferences and workshops, and to communicate results to a wide audience and through multiple mediums.
• Assist in the organisation of and participate in regular meetings and special workshops with the research team, designated members of staff and with other collaborators.
• Collaborate with colleagues in government and industry both on research and on taking methods developed towards wider use.
• Travel as necessary to meet with internal and external collaborators.
• Take initiative and make original contributions to the research programme wherever possible, and to contribute freely to the team research environment in a manner conducive to the success of the research project as a whole.

The successful candidate will have:

Essential

• PhD (or close to completion) or equivalent experience in statistics, machine learning, or a related discipline.
• Excellent written and 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.
• Ability to collaborate successfully with colleagues in government and industry.
• Ability to work as a member of a team.
• Ability to lead one’s own work, including planning and execution, and to prioritise work to meet deadlines.
• Ability to organise working time, take the initiative, and carry out research independently, under the guidance of the PI.

Desirable

• Experience in forensic science would be useful but is not required.
• Specialist expertise in a relevant area of methodology, including Bayesian modelling and causal inference.
• Experience of collaboration with government, or with analyst teams in other sectors outside academic research.
• Experience of collaboration with other academic disciplines.

Terms and Conditions

This full-time post is offered on a fixed-term basis of up to 3 years. We are happy to talk flexible working.

The annual Salary is £35,000 - £41,000.(dependent on skills and experience), plus an excellent benefits.package (https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits).

Application procedure

If you are interested in this opportunity, please click the apply button below and submit your CV, with contact details for your referees and a covering letter. If you have questions or would like to discuss the role further with a member of the Institute’s HR Team, please contact them on 0203 862 3394 or email [email protected] who would like to submit their application in a different format please email [email protected].

Closing date for applications: 19 January 2020

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, religion or belief or sexual orientation. Reasonable adjustments are available to support candidates through the application and interview process. Happy to Talk Flexible Working

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