Postdoctoral Research Associate, Computational Modelling for Housing Policy

Alan Turing Institute London United Kingdom Research Programmes

Company 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.

Position

The Public Policy research programme works alongside policy-makers to explore how data-driven public service provision and policy innovation might help to solve long running societal problems. We also work hand-in-hand with public sector organisations and citizens to develop practice-based ethical standards for the responsible development and use of data science and AI. Our dynamic group works closely with the UK government, as well as international organisations like the United Nations, the Council of Europe, and the European Commission.

As part of its growing leadership in data science and AI for the public sector, the Public Policy programme is strengthening its analytic capabilities by setting up a substantial programme of research in modelling for policy. This programme of research concentrates on studying pressing societal issues that could benefit from policy interventions and on constructing robust, empirically-informed models to identify the most beneficial policy measures. Our aim is to build tools and models that government partners can use to create better public policies.

ROLE PURPOSE

We are looking to hire an outstanding computational social scientist with a modelling background in methods that are relevant for analysing and designing housing markets and policy interventions, for example, agent-computing and geospatial analysis. The post-holder will join the Public Policy programme and will be a part of a multidisciplinary team of data scientists and modellers focused on developing a new programme of research in policy modelling.

The aim of this role is to develop data-rich and theoretically grounded models of the socio-economic and legal mechanisms that determine housing-market dynamics (e.g., price dynamics, bubbles, affordability crises, ownership inequality, etc.). The candidate will have experience in sourcing different types of large-scale datasets (this may include non-structured ones), as well as in pre-processing, analysing, and coupling the datasets with highly disaggregated computational models through adequate parameter estimation methods. The PDRA will also engage with government stakeholders, so having some experience regarding the viability and limitations of policy interventions is ideal. They will report to the Public Policy programme’s Head of Computational Social Science Research and will work closely with the other members of the research team.

DUTIES AND AREAS OF RESPONSIBILITY

  • To develop highly-resolved models of the socio-economic and legal mechanisms that determine housing-market dynamics. Such models should take full advantage of different types of large-scale data and should facilitate the experimentation of different types of policy interventions.
  • To identify and curate data sources that can be used to calibrate/estimate and validate the models.
  • To design and implement realistic policy intervention experiments, and translate the results into intuitive lessons for policymakers such as local councils and regional authorities.
  • To work with other Postdoctoral Research Associates across the Policy Modelling research group and the Public Policy programme.
  • To develop work plans to ensure timely delivery of objectives and assist with quarterly grant reports.
  • To build and maintain relationships with policy-makers and socio-economic modelling groups as part of the research project’s external engagement strategy.
  • To prepare research outputs that are tailored to a diverse audience, ranging from policy-makers to academic researchers, civil society, and the general public.
  • To present papers and research outputs at external conferences and events.

Requirements

  • A PhD or equivalent level of professional experience in any quantitative discipline related to
  • A solid track record conducting innovative computational research to study socioeconomic systems and their dynamics.
  • Experienced in working with large-scale datasets from various sources and formats.
  • Outstanding computational skills to analyse large-scale data and to produce efficient and well-documented agent-computing models.
  • Expertise in different calibration/estimation methods for agent-computing models. This should demonstrate critical thinking about choosing or developing empirical strategies that exploit the characteristics of the data and the model/problem at hand.
  • A proven ability to collaborate successfully in a multidisciplinary environment and to manage delivery of projects.
  • A record of scientific publication, which may include journal articles, book chapters, and scientific advisory reports/white papers, that is suitable to career stage and appointment level

Please see the Job description attachment for a full breakdown of the duties and responsibilities as well as the person specification.

Other information

TERMS AND CONDITIONS

This is a full-time post on a 2-year fixed term contract length. The annual salary is £37,000 to £42,000 (dependent on skills and experience) plus excellent benefits, including flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits.

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant with a salary of £34,500 per annum.

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; covering letter that outlines how you meet the job specifications; a list of publications as well as a sample piece of writing (a journal article, conference proceeding, book chapter, or equivalent); and contact details for two referees. If you have questions about the role or would like to apply using a different format, please contact us on email recruitment@turing.ac.uk.

CLOSING DATE: Sunday 17 October 2021 at 23:59.

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 recruitment@turing.ac.uk quoting the job title.

EQUALITY, DIVERSITY AND INCLUSION

The Alan Turing Institute is committed to creating an environment where diversity is valued, and everyone is treated fairly. 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.

Reasonable adjustments to the interview process can also be made for any candidates with a disability.

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.

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The Alan Turing Institute is committed to a policy of equal opportunities for its students, staff and applicants. In order to monitor the operation of this policy it is necessary to collect certain special categories of information from job applicants. The data collected here forms a confidential statistical record used solely for the purpose of monitoring the effectiveness of this policy. The information that you provide in this form is collected, maintained and stored securely in accordance with the General Data Protection Regulation and will only be shared with the HR team and the hiring manager involved in the recruitment process. Data used for statistical monitoring will be anonymised before being published outside of the HR Team. For information on how we use your special category data and how long we retain it for please refer to our recruitment privacy notice here. All personal information will be treated in accordance with the principles of the Data Protection Act (2018).

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