Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Research Associate in Physics-Informed Machine Learning for Crowd Dynamics

Economicsnetwork
Edinburgh
2 days ago
Create job alert
Overview

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.


Qualifications

  • 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.

Apply Before: 15/10/2025, 23:59


£41,064 to £48,822 per annum


#J-18808-Ljbffr

Related Jobs

View all jobs

Research Associate in Physics-Informed Machine Learning for Crowd Dynamics

Research Associate in Physics-Informed Machine Learning for Crowd Dynamics

Research Associate in Physics-Informed Machine Learning for Crowd Dynamics

Postdoctoral Research Associate in Biophysics and Machine Learning for Tumoroid Analysis

Postdoctoral Research Associate in Biophysics and Machine Learning for Tumoroid Analysis

Heilbronn Research Fellowships in Pure Mathematics, Data Science, and Quantum Computing

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.