Research Associate, Human Mobility

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

We invite applications for one full-time or multiple part-time postdoctoral research associate(s) to join the Unparameterised multi-modal data, high order signatures, and the mathematics of data science (DataSıg) team. Through collaboration between leading mathematicians and domain scientists, the DataSıg programme has created a wide array of computational tools for the analysis of complex multimodal data streams. These tools leverage the power of deep learning alongside the well-understood mathematics of rough path theory, and have shown state-of-the-art performance for irregularly sampled multivariate time series problems (i.e. messy data). In particular, rough path theory has led to recent advances in data compression, kernel methods, neural differential equations and stochastic analysis.

The programme, led by Professor Terry Lyons FRS, is funded by the EPSRC and brings together research groups from Imperial College London, UCL and the University of Oxford with a hub at the Alan Turing Institute https://www.turing.ac.uk. More details of the DataSıg project can be found at https://www.datasig.ac.uk.

The main focus of the DataSıg programme is to develop the theoretical and computational aspects of rough path techniques and to demonstrate their effectiveness in a wide range of applications. This covers a range of different research directions:

  • Studying and developing the principles underlying rough path theory as well as relevant aspects of data science.
  • Producing a generic set of computational tools that can be tailored to specific problems and hardware.
  • Applying rough path methodologies in collaboration with external partners, to real-world applied challenges (ACs) within the areas of Computer Vision, Mental Health, Radio Astronomy, Human Machine Interfaces and Human Mobility. Each of these areas is supported by at least one PDRA.

The most recent applied challenge associated with the DataSıg programme is Project Odysseus – a collaborative venture within the Alan Turing Institute, led by Dr Theo Damoulas, which seeks to better understand human mobility within London. This project has a broad range of objectives including:

  • To combine multiple data sources with a variety of spatial and temporal resolutions to provide an overall view of the city’s level of activity.
  • To identify relationships between mobility, transportation and economic activity in different areas of London.
  • To aid London authorities and UK policy-making as the country moves into its recovery period.
  • To further develop expertise in tackling engineering challenges with large-scale and noisy data.

Project Odysseus builds upon existing infrastructure, such as the live traffic camera feeds successfully used in the project ‘Near Real-Time Social Distancing in London’ to estimate social distancing adherence. In addition, the team has delivered tools to local authorities that make these large-scale traffic datasets accessible in real-time. However due to the challenges inherent in video and spatial time series data, a new generation of inferential methods are needed to support this progress.

We anticipate that the techniques and methodologies developed in Project Odysseus will be applicable to future projects in the areas of urban science that align with the Turing research programme on Data-Centric Engineering.

ROLE PURPOSE

We are seeking to recruit either one full-time or multiple part-time postdoctoral researcher(s) to join the DataSıg team; working with the principal investigator Terry Lyons (Oxford and Turing) and co-investigators, Harald Oberhauser (Oxford), Thomas Cass (Imperial) and Hao Ni (UCL). The successful candidate(s) will be based at the Alan Turing Institute in London.

The project will involve working closely with members of the DataSıg team to further develop rough path techniques as they relate to data science and to identify areas of opportunity within the “Human Mobility” applied challenge. The latter research direction will be made possible through a partnership with the Alan Turing Institute’s Data-Centric Engineering programme and contributes to Project Odysseus, which aims to better understand mobility, transportation and traffic activity over the city of London. A particular focus of this project is spatiotemporal data (that is, time series data with a spatial component).

DUTIES AND AREAS OF RESPONSIBILITY

The successful candidate will work closely with project investigators based at the Alan Turing Institute with the aim:

  • To manage their own academic research and administrative activities. This involves small scale project management and coordinating multiple aspects of work to meet deadlines
  • To adapt existing and develop new research methodologies
  • To prepare working theories and analyse qualitative and/or quantitative data from a variety of sources, reviewing and refining theories as appropriate
  • To collaborate in the preparation of research publications and book chapters
  • To act as a source of information and advice to other members of the group on methodologies or procedures
  • To undertake any training and or professional development

Other duties:

  • Teaching and related activities may be required as part of collaboration work
  • To support the Principal Investigator and research group in the design and development of the research programme.
  • To ensure compliance with secure handling of data and health and safety in all aspects of work.
  • To participate in and develop internal and external partnerships, for example to identify sources of funding, generate income, obtain projects, or build relationships for future activities.

Requirements

Essential

  • Research associate level: Holds a PhD or equivalent level of professional qualification in a mathematically related discipline.
  • Research Assistant level: Near completion of a PhD or equivalent level of professional qualification in a mathematically closely related discipline.
  • A solid background in one or more of the following: Mathematics, Scientific Computing, Rough Path Theory, Computational Statistics, Machine Learning, High-Performance Computing
  • Experience in design, development and implementation of research software libraries, ideally using one of the following: Python, C++, R, Julia and their associated frameworks.
  • Track record of the ability to initiate, develop and deliver high quality research aligned with the research strategy indicated by the PI and any industrial stakeholders and to publish in peer reviewed journals and conferences
  • Excellent written communication skills, including the ability to write for publications, present research proposals and results, and represent the research group at meetings.
  • Ability to organise and prioritise own work with minimal supervision
  • The ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines.
  • Ability to carry out original research and to produce published research papers
  • A developing track record in producing high quality academic publications.
  • Ability to write research reports and papers in styles accessible to both academic and lay audiences.

Desirable

  • Specialised knowledge in areas related to rough paths or spatiotemporal data.
  • Creative approach to problem solving

Please see Job Description attachment for a full breakdown of our Person Specification.

Other information

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 and contact details for your referees. If you have questions about the role or would like to apply using a different format, please contact them on 0203 862 3340, or email recruitment@turing.ac.uk.

CLOSING DATE FOR APPLICATIONS: Sunday 08 August 2021 at 23:59.

TERMS AND CONDITIONS

This full-time post is offered on a fixed-term basis for two years with an ideal start date of 01 September 2021. The annual salary is £37,000-£42,000 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 at a salary of £34,500 per annum.

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 will be made for any candidates with a disability.


Please note all offers of employment are subject to obtaining and retaining the right 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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