Research Associates – Evaluating Complex Forensic Evidence (Bayesian Methodology/Causal Bayesian Inference)

Country: United Kingdom;

City: London

Vacancy added: 01.04.2019

Employer:

Vacancy type: PostDoc vacancy;

Resumes due: 16.05.2019

 

JOB DESCRIPTION

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.

The Role

We are seeking up to two Researchers who will be part of a team of top Bayesian, decision theory and causal inference academics, and be based at The Alan Turing Institute. The research team includes, Anjali Mazumder (co-PI), Amy Wilson (co-PI), Jim Smith (Warwick), Philip Dawid (Cambridge), Henry Wynn (LSE), and colleagues across Europe and the US. Researchers will meet regularly with the research team and should expect to engage with domain experts.

The evaluation of forensic evidence often involves complex scenarios consisting of more than one evidence type, each with an associated uncertainty, and a hierarchy of propositions to be addressed. Data to calculate probabilities can be limited as case circumstances are often unique and propose multiple causal and decision-making pathways.

Informal enquiries may be made to the PIs: Amy Wilson Amy.L.Wilson@ed.ac.uk and Anjali Mazumder at amazumder@turing.ac.uk.

DUTIES AND RESPONSIBILITIES

  • Perform high quality research in Bayesian 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.

PERSON SPECIFICATION

Essential

  • PhD (or close to completion) or equivalent experience in statistics, machine learning, (quantitative) philosophy or a related discipline
  • Ability to programme in R and/or Python.
  • 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

  • Specialist expertise in a relevant area of methodology, Bayesian modelling and population statistics (R1), Bayesian modelling and causal inference (R2)
  • Experience of collaboration with government, or with analyst teams in other sectors outside academic research.
  • Experience of collaboration with other academic disciplines.
  • Interest in forensic science and/or legal reasoning.

Application procedure

If you are interested in this opportunity, click the apply button below. For more information about the role and a full job description and job specification please visit the Alan Turing Institute career page.

Closing date for applications: 16 May 2019

 
Where to send resume: