Research Fellow in AI-Augmented Spatial Analysis (Fixed Term)
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Research Fellow in AI-Augmented Spatial Analysis (Fixed Term)
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Fixed-term: The funds for this post are available for 3 years in the first instance.
We invite applications for a Postdoctoral Research Fellow to join the Lab of Interdisciplinary Spatial Analysis (LISA) in the Department of Land Economy, University of Cambridge. This position is funded by the City University of Hong Kong and will be held at Cambridge. The Fellow will work under the supervision of the Principal Investigator and Director of LISA, with a view to developing LISA's research capacity in AI-augmented spatial analysis.
The Fellow is expected to lead the development and application of machine learning and artificial intelligence methods in spatial analysis within the Department. Land Economy is defined as the multidisciplinary study of how society interacts with the environment, both natural and built. The Department includes researchers from economics, law, planning, public policy, finance, real estate and engineering. LISA supports spatial research across these fields, with a focus on GIS and its applications in environmental, urban, housing, and institutional studies.
The Fellow will contribute to ongoing research at LISA, in particular the eMotional Cities project, a Horizon 2020-funded collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret and explain the spatial patterns already identified. The Fellow will help advance this work by generating actionable insights for policymakers addressing mental health and well-being in both urban and rural contexts. The Fellow is also expected to work closely with the PI to prepare and submit applications for major funding opportunities in the UK and EU, with the aim of securing large-scale grants to scale up the eMotional Cities initiative. This will require familiarity with interdisciplinary collaboration, research design, and proposal development.
Candidates should have a PhD (submitted or nearly submitted at the time of application) in a field relevant to urban economics, spatial econometrics, geography, urban planning, or data science, with a strong quantitative focus. Applicants should have experience in spatial analysis and/or machine learning methods, and an interest in applying these tools to urban and housing policy questions.
The Fellow should demonstrate potential for producing high-quality research and a strong commitment to empirically grounded, quantitative, and interdisciplinary work. In addition to academic outputs, the successful candidate will be expected to play an active role in the development of collaborative research proposals, including those submitted to major international and national funders such as Horizon Europe, UKRI, and the ESRC. Strong communication and coordination skills are essential, as the role involves sustained engagement with a wide range of stakeholders¿including academic collaborators, policy makers, industry partners, and civil society organisations¿often within large, multi-institutional research consortia.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. We particularly welcome applications from candidates from a BAME background for this vacancy as they are currently under-represented at this level in our department.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Please upload the following: - a full Curriculum Vitae including a list of publications - a cover letter including a statement of your research, your relevant work experience and qualifications, and in general how your profile fits the position using no more than 1,500 words - the contact details of two referees.
After shortlisting, where you have given permission, your nominated referees will be asked to provide a reference via the on-line system.
Closing date is midnight on Wednesday 20th August 2025. Interviews will be held soon after the closing date. Please quote reference JP46689 on your application and in any correspondence about this vacancy. Informal queries about this position may be directed to Professor Helen Bao, Principal Investigator of the project and Director of LISA. hxb20@cam.ac.uk.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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