Leiden University invites applications for a fully-funded PhD position focused on the development of efficient artificial intelligence solutions for traffic management and decision support systems. This interdisciplinary project sits at the intersection of AI, machine learning, and real-world traffic operations, aiming to leverage foundation models such as large language models (LLMs) to enhance real-time decision-making in road traffic management. The research will address the integration of multimodal and instruction-tuned foundation models with operational challenges faced by traffic operators, municipalities, and mobility service providers. Key research activities include adapting LLMs for spatial-temporal data and traffic control domains, developing hybrid AI architectures that combine symbolic domain knowledge, real-time data streams, and probabilistic inference, and designing decision support tools capable of natural language interaction, scenario simulation, and action explanation. The project will also investigate the efficiency, robustness, generalization, and ethical implications of deploying foundation models in safety-critical infrastructure. The PhD position is a joint initiative between Leiden University and Technolution, a leading Dutch technology innovator known for its MobiMaestro traffic-management platform and FlowCube smart AI traffic camera. The successful candidate will work within the Leiden Institute of Advanced Computer Science (LIACS), a top-ranked computer science department in the Netherlands, and collaborate with a consortium of academic and industry partners. Responsibilities include conducting original research, publishing in peer-reviewed journals and presenting at international conferences, completing a PhD thesis within four years, engaging with other researchers and developers, and assisting in teaching activities. The position offers a supportive, diverse, and international work environment located in the heart of the Bio Science Park, with access to excellent facilities and career development opportunities. The employment package includes a competitive salary (€3,059–€3,881 gross per month), holiday and end-of-year bonuses, pension scheme, full reimbursement of public transport commuting costs, flexible working hours, options for sabbatical or paid parental leave, hybrid working arrangements, home-working allowance, and a university-provided laptop. Applicants should hold or be close to completing an MSc in computer science, AI, or a related field, possess strong programming skills (Python, PyTorch), be familiar with modern ML frameworks and large-scale models, and have excellent analytical and communication skills. Fluency in English is required. The application deadline is December 18, 2025. For more information about LIACS and the application procedure, visit the provided university links. Enquiries can be directed to Prof. Rob van Nieuwpoort ([email protected]).

Leiden University invites applications for a fully-funded PhD position focused on the intersection of artificial intelligence, traffic management, and decision support systems. This research opportunity is part of a collaborative project between Leiden University and Technolution, embedded within a larger consortium involving both academic and industry partners. The successful candidate will join the Leiden Institute of Advanced Computer Science (LIACS), a leading computer science department in the Netherlands, and work closely with Prof. Rob V. van Nieuwpoort (Leiden University) and Tijs van Bakel (Technolution). The project aims to advance the application of foundation models, including large language models (LLMs), to support and enhance real-time decision-making in road traffic management. Research activities will include adapting and fine-tuning LLMs for spatial-temporal data and traffic control domains, developing hybrid AI architectures that integrate symbolic reasoning, real-time data streams, and probabilistic inference, and designing decision support tools capable of natural language interaction, scenario simulation, and action explanation. The study will also address efficiency, robustness, generalization, and ethical implications of deploying foundation models in safety-critical infrastructure. As a PhD candidate, you will conduct original research, publish in peer-reviewed journals, present at international conferences, and complete a PhD thesis within four years. You will collaborate with researchers and developers at LIACS, Technolution, and the broader project consortium, and may assist in relevant teaching activities. The position offers a stimulating and international environment, with access to the Bio Science Park, one of Europe’s largest science parks, and a vibrant academic community. Applicants should hold (or be close to completing) an MSc in computer science, AI, or a related field, possess strong programming skills (Python, PyTorch), and have experience with modern machine learning frameworks and large-scale models. An interest in interdisciplinary research, excellent analytical and communication skills, and fluency in English are essential. The university values diversity and inclusivity, and encourages candidates from all backgrounds to apply. The position is fully funded, offering a competitive salary (€3,059–€3,881 gross per month), holiday and end-of-year bonuses, pension scheme, full reimbursement of public transport commuting costs, flexible working hours, options for sabbatical or paid parental leave, hybrid working arrangements, home-working allowance, and a university-provided laptop. The initial contract is for one year, with extension to four years upon positive evaluation. To apply, submit your application via the official university careers portal before December 18, 2025. For academic inquiries, contact Prof. Rob van Nieuwpoort at [email protected]. For procedural questions, email [email protected]. More information about the application process and employment conditions is available on the university website. This is an excellent opportunity for motivated researchers interested in cutting-edge AI applications for traffic management and decision support, within a supportive and innovative academic environment.