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Alan Turing Institute - Research Associates (x3) - The Science of Cities and Regions

Closing date: 
Wednesday, 12 April 2023

The Alan Turing Institute

The Alan Turing Institute is seeking to appoint three Research Associates - The Science of Cities and Regions.


We are looking to appoint 3 Research Associates to The Science of Cities and Regions Programme. The Programme seeks to advance its four core missions (mobility, land use, liveability, and digital twins) which are of fundamental importance to the Grand Challenges of the Institute; to develop a technology platform that enables the delivery of the missions; and to build social infrastructure around the Science of Cities and Regions. These goals are only possible by building further capacity at the Turing; increasing its relevance to stakeholders and university partners; consolidating its connectivity to other Turing programmes and activities; and producing world-leading applied research and innovation.

You will look for opportunities to focus on specific datasets and problems e.g. working with partners to discover the novel added value to inform interventions and policy planning decisions. You will have  unique opportunities to work with the Data and Digital teams in government and other national and local agencies with a strong social impact agenda e.g. in relation to net zero or levelling up communities.


  • Develop and implement models of mobility, land use, population behaviour and change.
  • Undertake analysis of large and complex social and spatial datasets, deploying contemporary machine learning approaches.
  • Work with as part of of the research team to design ‘what if’ scenarios underpinned by Digital Twin technology, creating solutions to inform future plans and policy interventions.
  • Contribute new functionality to the growing ecosystem of open source technology.
  • Collaborate with software developers and data scientists to augment parts of the planning process and make it more data driven.
  • Process datasets representing roads and active travel infrastructure such as pavements and cycleways, using machine learning to simulate and evaluate changes for maximum public benefits.


  • PhD or equivalent level of professional experience in geography or a related discipline
  • Skills and experience in the analysis of spatial data and in the manipulation of spatial data
  • Evidence of the ability to explore and understand social phenomena through the interrogation of quantitative spatial.
  • Knowledge of data science: data visualisation, machine learning, statistical modelling.
  • Strong computational skills (e.g., proficient at coding in chosen language(s).
  • Ability to communicate complex, specialist or conceptual information clearly and persuasively to diverse audiences.
  • Ability to work with others, especially postdocs, data scientists, 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.

For further details including how to apply, please see:

Should you have any queries, please email

Closing date: 12 April 2023 at 23:59 BST

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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