Research Associate in Physics-Informed Machine Learning for Crowd Dynamics

University of Edinburgh; City of Edinburgh; On-site; GBP 41,000 - 49,000; Full time

Job summary

A leading research university in Edinburgh is seeking a Postdoctoral Research Associate for an EPSRC-funded project focused on developing a real-time simulator for crowd dynamics using machine learning techniques. The role involves collaboration with PhD students and industry partners, offering opportunities for impactful research in public safety and urban planning. Competitive salary and benefits package included.

Benefits

Competitive salary

Generous holiday entitlement

Comprehensive pension scheme

Staff discounts

Family-friendly initiatives

Qualifications

• PhD (or near completion) in a relevant field.
• Strong expertise in machine learning.
• Understanding of mathematical modeling.

Responsibilities

• Develop a physics-informed machine learning pipeline.
• Collaborate closely with a PhD student.
• Simulate real events using the developed simulator.

Skills

Strong expertise in machine learning and scientific computing

Solid understanding of mathematical modelling

Proficiency in scientific programming (Python, Fortran, C++)

Strong analytical and problem-solving skills

Communication skills

Education

PhD (or be near completion) in Engineering, Physics, Applied Mathematics, Computer Science, or a related field

Job description

Overview

Grade UE07 £41,064 - £48,822 per annum

College of Science & Engineering / School of Engineering / Institute for Multiscale Thermofluids / Machine Learning, Computational Engineering, Crowd Dynamics

Full-time: 35 hours per week

Fixed Term: from 1st March 2026, for up to 36 months

We are looking for a talented, creative, and experienced Postdoctoral Research Associate to join the EPSRC-funded project FLOCKS (Fluid dynamics-Like Open-source Crowd Knowledge-driven Simulator).

The Opportunity

Designed in close collaboration with industry leaders, FLOCKS aims to create the world's first real-time, open-source simulator of large, dense crowd dynamics. The simulator will have applications in public safety, urban planning and event management. The research will focus on developing a physics-informed machine learning pipeline to derive governing equations and boundary conditions for macroscopic crowd models from synthetic and real-world data. Close collaboration with a dedicated PhD student, who is developing physics-based models and generating synthetic datasets, will fuel the machine learning framework while also offering a valuable opportunity for mentorship. Thanks to its partnerships with world-leading experts in crowd safety engineering and open-source software development, the project will have a direct impact on real-world applications relating to public safety, urban planning and event management. A final demonstrator will simulate iconic local events (e.g. Hogmanay on Princes Street, an Edinburgh derby football match, or a Murrayfield Stadium concert) using pre-captured datasets to demonstrate the simulator's predictive power and direct relevance to these applications. This is an excellent opportunity for an experienced researcher interested in machine learning, mathematical modelling, and complex systems.

Your skills and attributes for success

• PhD (or be near completion) in Engineering, Physics, Applied Mathematics, Computer Science, or a related field.
• Strong expertise in machine learning and scientific computing.
• Solid understanding of the mathematical modelling of physical systems.
• Proficiency in scientific programming (e.g., Python, Fortran, C++).
• Strong analytical, problem-solving, and communication skills.

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As a valued member of our team you can expect

• A competitive salary
• An exciting, positive, creative, challenging and rewarding place to work.
• To be part of a diverse and vibrant international community
• Comprehensive Staff Benefits, such as a generous holiday entitlement, competitive pension schemes, staff discounts, and family-friendly initiatives. Check out the full list on our staff benefits page and use our reward calculator to discover the total value of your pay and benefits

Equality, diversity and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

Prior to any employment commencing with the University you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.

The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.

Key dates

The closing date for applications is 15 October 2025.

Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browser's local time zone.

About Us

As a world-leading research-intensive University, we are here to address tomorrow's greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.

About the Team

Engineering has been taught at Edinburgh in one form or another since 1673. In 2002, the present School of Engineering was formed from the previously existing departments of Chemical Engineering, Civil Engineering, Electronics and Electrical Engineering, and Mechanical Engineering. Since then, the School has grown rapidly, now having the largest number of students among the seven Schools in the College of Science and Engineering, offering undergraduate degree programmes across all disciplines and taught Masters courses in niche areas. All of the undergraduate degree programmes are accredited by the relevant professional institutions.

The School of Engineering addresses diverse complex challenges across the entire field of engineering, at the micro- and macro/global scales. At the microscopic scale, its research supports the design and deployment of novel nanotechnology and devices for biological monitoring and medical diagnosis; at the macro/global scale, it optimises the security and sustainability of the built environment and develops engineering solutions to climate change issues. In REF 2021 the joint submission from the University of Edinburgh and Heriot-Watt University to General Engineering was ranked 1st in Scotland and 3rd in the UK for quality and breadth of research. The ranking cited is based upon the breadth and quality of research which apply standard formula (as used by the Times Higher Education) to the REF 2021 results.

The School has a strong track record in producing more than 50 technology spin-outs and developing industry links that enable our graduates to build career-long relationships. Current research income in the School was c.£22.0M in 2020/21.

We aim to ensure that our culture and systems support flexible and family-friendly working and recognise and value diversity across all our staff and students. The School has an active programme offering support and professional development for all staff; providing mentoring, training, and networking opportunities.

The School of Engineering holds a bronze Athena SWAN award, in recognition of our commitment to advance gender equality in higher education & research.

Further information, including details of undergraduate & postgraduate taught programmes: www.eng.ed.ac.uk