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.

SHOCKS AND RESILIENCE RESEARCH PROJECT
Measuring policy impact in the Covid-19 crisis and building resilience against future shocks.

The Covid-19 crisis has highlighted how vulnerable societies and governments are to shocks. This vulnerability is exacerbated by the propensity to design policy for narrow siloes relating to singular policy areas and government departments, without adequate consideration of the interdependencies between them and the interconnected nature of local and global societies. The pandemic has brought into focus that resilience in one policy area (e.g. health) can come at the cost of resilience in another (e.g. the economy). The overall aim of this large-scale, 2-year research project is to develop a better understanding of resilience in interconnected health, social, and economic systems and to use this understanding to identify robust policy measures.

The project brings together multidisciplinary expertise from across the Turing community, including in health, public policy, economics, and urban analytics. We are hiring nine postdoctoral research associates for this project, who will work collaboratively to develop a rigorous understanding of societal responses to shocks and a clear strategy for how to engender policy resilience. To achieve our aims, we will require reliable, consistent, real-time, fine-grained data sources, as well as integrative, highly-granular models that bring together policy areas and cross disciplinary boundaries.

The Shocks and Resilience project consists of the following five work packages, and we are hiring nine postdoctoral research associates (PDRAs) in total:

1. Modelling COVID-19 (2 PDRAs)
2. Learning causality and dynamics in interconnected systems (2 PDRAs)
3. Spatial modelling (2 PDRAs)
4. Generalised models for resilient policy-making (2 PDRAs)
5. Engagement, implementation, and dissemination to policy-makers (1 PDRA)

We recommend reading the project’s website and all the job descriptions related to this project. Taking the time to do so will ensure that you are applying for the post that most closely matches your interests and experience.

This project is supported entirely by public funds, through Wave 1 of the UK Research and Innovation Strategic Priorities Fund, under EPSRC Grant EP/T001569/1.

Work package 2: Learning causality and dynamics in interconnected systems (x2 PDRAs)

This work package focuses on developing new theory, methods, tools, and practices for understanding causality and dynamics in complex interconnected systems under conditions of uncertainty. A crucial part of this package is discovering ways to allow for feedback that is able to adapt and update as new data arrives. We aim to develop rigorous new statistical theory as well as computational methodology that allows for the incorporation of physical, economic, and biological principles into machine learning algorithms.

ROLE PURPOSE

We are looking to recruit two postdoctoral research associates to work collaboratively: a Statistics Postdoctoral Research Associate, who will work on developing rigorous new statistical theory; and a Machine Learning Postdoctoral Research Associate, who will work on developing computational methodology that allows incorporation of physical, economic or biological principles (or prior knowledge) into machine learning algorithms and/or distilling such principles directly from data.

DUTIES AND AREAS OF RESPONSIBILITY

• To develop a rigorous theoretical understanding of causation in complex interconnected systems (Statistics Postdoctoral Research Associate).
• To develop a rigorous and computationally efficient methodology for constraining machine learning models with physical/social/biological principles (Machine Learning Postdoctoral Research Associate) and/or learning such principles from complex data.
• Work with the eight other postdoctoral research associates across the shocks and resilience project to embed new methods within specific research initiatives.
• Collaborate with the senior academics overseeing this research project, as well as the nine other postdoctoral research associates, in pursuing the research agenda described above.
• Develop work plans to ensure timely delivery of objectives and assist with quarterly grant reports.
• Build and maintain relationships with external statistics/machine learning groups as part of the research project’s external engagement strategy.
• Prepare research outputs that are tailored to a diverse audience, ranging from statisticians, mathematicians and applied researchers, civil society, and the general public; present papers and research outputs at external conferences and events.
• Work in close coordination with the Turing’s Health and Public Policy Programmes to maximise the project’s influence on ongoing policy debates.

If appointed at a Senior Postdoctoral Research Associate level, the post-holder will have additional responsibilities, such as:

• To oversee the work of other Postdoctoral Research Associates who are conducting research in related areas.
• To define the research direction in collaboration with the PIs of the Shocks and Resilience project.
• To take the lead on writing up findings as they emerge, producing reports, and developing publications in peer reviewed journals, in collaboration with the research team.

Essential:

• PhD or equivalent level of professional experience in theoretical mathematics, statistics, machine learning or a related discipline;
• A research background in pure or applied statistics, causal inference, Bayesian methods (for the Statistics Postdoctoral Research Associate role). We will consider candidates for an appointment at a Senior Postdoctoral Research Associate level if they have significant postdoctoral research experience (3+ years);
• A research background in machine learning for physics, biology or social science (for the Machine Learning Postdoctoral Research Associate role). We will consider candidates for an appointment at a Senior Postdoctoral Research Associate level if they have significant postdoctoral research experience (3+ years);
• Outstanding computational skills (e.g. proficient at coding in chosen language(s)), (for the Machine Learning Postdoctoral Research Associate role);
• Ability to communicate complex, specialist or conceptual information clearly and persuasively to diverse audiences;
• Ability to work with others, especially postdocs, research assistants, and PhD students;
• A proven ability to collaborate successfully in a multidisciplinary environment and to manage delivery of projects;
• Ability to organise and prioritise own work with minimal supervision;
• Ability to carry out original research and to produce published research papers;
• Ability to identify, develop and apply new concepts, techniques and methods ;
• Commitment to Equality Diversity and Inclusion principles and to the Organisation values.

Desirable:

• Knowledge of topics and theories in health or epidemiology;
• Knowledge/understanding of the UK government and policy-making landscape;
• Experience in interacting with policy-makers and translating data-driven findings into meaningful insights and policy-focused reports.

TERMS AND CONDITIONS

These full-time posts are offered on a fixed-term basis for a period of two years. The annual salary is £35,000 to £41,000 (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 are appointed at a Senior Postdoctoral Research Associate level will have a salary within the range of £42,000 to £49,000 per annum.

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within a salary range of £32,000 to £34,000 per annum.

This job description is written at a specific time and is subject to change as the demands of the Institute and the role develop. The role requires flexibility and adaptability, and the post holder needs to be aware that they may be asked to perform tasks and be given responsibilities not detailed in this job description.

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 020 3862 3575 or email recruitment@turing.ac.uk.

CLOSING DATE FOR APPLICATIONS: 6 December 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 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.