The Alan Turing Institute

Launched in November 2015, the Alan Turing Institute is the national institute for data science and artificial intelligence. Our mission is to make great leaps in research to change the world for the better.

The Institute is headquartered at The British Library, and brings together researchers from a range of disciplines – mathematics, statistics, computer science, engineering and social sciences, – from thirteen leading universities and industry partners.

The Role

As a Post-Doctoral Research Associate (RA) you will work closely with PIs on projects across applied areas of data science and artificial intelligence. We are looking for those who have a clearly indicated interest in Health, Urban Analytics, Complex Engineering Systems, and Policy (including the research priorities of government departments, such as the Home Office or Ministry of Justice).

We welcome candidates who can start within the next month or two, including those who will submit their PhD thesis in the near future.

Main Duties and Responsibilities

  • Contribute statistical and machine learning skills to the various elements of the project.
  • Working closely with the PI, Co-Is and domain experts to develop a good understanding of the challenges in this domain and potential solutions.
  • Support the Principal Investigator and research group in the design and development of the research programme.
  • Conduct studies of related literature and research to support the design and implementation of projects and development of reports, ensuring conceptual relevance, comprehensiveness, and currency of information.
  • Conduct a specified programme of research to advance the aims of the project under the supervision and direction of a Principal Investigator, working with the Institute team, including research assistants, research associates, software engineers, data scientists and PhD students.
  • Engage in appropriate training and professional development opportunities as required by the Principal Investigator.
  • Write and publish articles in peer-reviewed journals/digests that highlight findings from research ensuring consistency with the highest standards of academic publication and showcasing the Institute’s research leadership

Skills and experience

Essential

Candidates must be able to demonstrate, through examples, the below capabilities:

  • A PhD degree or equivalent professional experience in a field with significant use of both computer programming and advanced statistical or numerical methods.
  • Experience managing, structuring, and analysing research data.
  • Experience managing and evaluating the ethical implications of a project.
  • Experience managing and organising the parameters and results of computational experiments.
  • Fluency in one or more modern programming languages used in research in data science and artificial intelligence. (We particularly work in R, Python, and modern C++, but demonstrable use of other programming languages for research, together with a facility for learning new languages, is most welcome.)
  • An understanding of the importance of good practices for producing reliable software and reproducible analyses (e.g. version control, issue tracking, automated testing, package management, literate analysis tools such as Jupyter and Rmarkdown)
  • Demonstrated enthusiasm and ability to rapidly assimilate new computational and mathematical ideas and techniques on the job, at a more than superficial level, and apply them successfully.
  • Excellent written and verbal communication skills, including experience in the visual representation of quantitative data, the authoring of research papers or technical reports, and giving presentations or classes on technical subjects.
  • Ability to lead one’s own work independently, including planning and execution, and to collaborate productively as part of a team.

Desirable

  • Machine learning.
  • Mathematical and computational modelling of complex systems.
  • Computational statistics, particularly Bayesian modelling.
  • Logic, planning, verification, and automated reasoning.
  • User interface design and development with web technologies, especially for data visualisation and knowledge representation.
  • Experience working with confidential and sensitive data for research.
  • Working with databases and APIs for the acquisition of parameter information for models.
  • Exposure to mixed or qualitative research methods.
  • Experience using graphical methods and non-parametric tests.
  • Topological data analysis.
  • Hypergraph theory.
  • Information system design.

Contract Type

Fixed term up until 2023 for part time for those pursuing a part-time PhD, with possibility for extension (funding permitting); fixed term up until 2021 for full time, with possibility for extension (funding permitting).

To Apply:

If you are interested in this opportunity, please send your CV, with contact details for your referees and a covering letter to [email protected]. Along with a CV and covering letter, please submit a research output to support your application, for us to read before the interview. This might be a link to a selected research or technical paper, a technical blog post or a chapter of a thesis or dissertation, but we particularly encourage applicants to submit a link to a public version control tool such as GitHub containing an example analysis script or research software library they have made a significant contribution to. You will be asked questions on this output as part of the interview.

We encourage applications from those who are able to commence the post in November 2018 or as soon as possible thereafter.

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 3375 or email [email protected].

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.

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

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