Research Associates - Managing Uncertainty Government Modelling

Country: United Kingdom;

City: London

Vacancy added: 07.02.2019

Employer:

Vacancy type: PostDoc vacancy;

Resumes due: 04.03.2019

 

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 two full-time post-doctoral Research Associates (RAs) to work on the Turing Partnership Project “Managing Uncertainty in Government Modelling”. This is a collaboration between the University of Edinburgh (Chris Dent, PI), LSE (Henry Wynn),Exeter University (Peter Challenor) and Warwick University (Jim Smith).

Modelling and data science methodologies are widely used to support government policy, management and investment decisions. Three recent documents, the Aqua Book (Guidance on producing quality analysis for government, https://www.gov.uk/government/publicatio...), the Blackett Review of Computational Modelling, and the newly revised Treasury Green book stress the importance of high-quality data, sound statistical analysis and mathematical modelling in decision support. The need case is strengthened by reports from the National Audit Office and the project leads’ discussions with government (see, for example, http://hubnet.org.uk/filebyid/1130/Modelling_in_Public_Policy.pdf).

The project

This project responds to the above need by developing practical methods and tools for managing uncertainty in government modelling. The aim is to develop protocols for a wide range of analysts in the field to quantify and manage uncertainty in their own modelling, without the need to involve research experts in each individual project.

The project will proceed through a mixture of work on specific demonstrators provided by government departments, agencies and regulators with more general thinking on how such scientifically valid and widely applicable methods may be developed. Specific areas of modelling identified for study are valuing uncertain future liabilities and benefits (e.g. portfolio of clinical negligence claims, major infrastructure projects), planning allocation of resources over time (e.g. the national teacher supply model) and propagation of uncertainty through models (including use of statistical emulators/metamodels, exemplars including heat network planning).

Informal enquiries may be made to the PI (chris.dent@ed.ac.uk). The positions are for 2 years (24 months) The deadline for applications is the 4th March 2019

Main Responsibilities

  • To undertake research work related to the project.
  • To produce high-quality research publications documenting the results of the research, to publish these papers in relevant peer-reviewed scientific journals of international standing, and to present these results at conferences and workshops.
  • To hold regular meetings with designated members of staff and with other collaborators.
  • To collaborate with colleagues in government both on research and on taking methods developed towards wide use in government.
  • To travel as necessary to meet with external collaborators.
  • To 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

Essential

  • PhD (or close to completion) or equivalent experience in statistics, operational research or a related discipline.
  • Publication record in international journals, as appropriate to career stage.
  • 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.
  • 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, such as emulation of complex models, uncertainty quantification, structured expert elicitation, or Markov processes.
  • Experience of collaboration with government, or with analyst teams in other sectors outside academic research.
  • Experience of collaboration with other academic disciplines.

How to Apply

Further information about the Turing, the role, duties and responsibilities can be found on the Turing website and person specification here enclosed.

If you consider that you meet the criteria set out in the person specification and would like to apply for the role, please email your CV and cover letter to jobs@turing.ac.uk.

Application procedure

If you are interested in this opportunity, please send your CV, with contact details for your referees and a covering letter to jobs@turing.ac.uk. 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 jobs@turing.ac.uk.

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, gender reassignment, marital and civil partnership status, pregnancy, religion or belief or sexual orientation. Reasonable adjustments to the interview process can also be made for any candidates with a disability. 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.

Full details on the pre-employment screening process can be requested from HR@turing.ac.uk.

Closing date for applications: 4 March 2019

Interviews will take place: tbc

 
Where to send resume: