Join us at the STAR Lab

Our mission is to understand and demonstrate the potential of AI to facilitate decision processes and improve outcomes in complex socio-technical situations. Interested in an open or prospective position? See below for more information.

Master's Projects

Interested in one of these positions, or another idea for your master's thesis with our lab? See below how to apply.

Real world applications of AI optimisation algorithms

Data-driven optimisation. With companies like KLM, ORTEC, Picnic, TNO and Vanderlande.

Optimisation

Simulation

Uncertainty

Machine learning for combinatorial optimisation

Reinforcement or supervised learning to accelerate combinatorial optimisation solvers.

Optimisation

Data-driven agent-based simulation

ABM + RL to study migration, cities, policies and sustainability.


Simulation

Uncertainty

Acquiring CP models with interactive machine learning

From data to model with the help of human expert.


Optimisation

Learning to solve vehicle routing

Dynamic pickup-and-delivery, and other VRP problems with RL.


Optimisation

Uncertainty

Multi-agent RL for autonomous logistics

Comparing centralised and decentralised approaches.

Optimisation

Simulation

Decision focussed learning

End-to-end optimisation over a function acquired from data.


Optimisation

Uncertainty

AI for structural engineering

Analysing concrete, masonary and bridge designs with ML.


Simulation

Uncertainty

High performance ABM

Scaling ABM onto the DelftBlue supercomputer.


Simulation

Negotiation under culture

How does the optimisation problem change when considered in the cultural context?

Uncertainty

Optimisation

User interface of the Mesa "Python as ABM" open source project

What information about an ABM to present to the user? How does UX affect scientific enquiry?

Simulation

Net-zero energy markets

Distributed optimisation techniques for electricity market coordination.


Uncertainty

Optimisation

Open Positions and Projects

The lab reflects a wide body of work by dedicated and passionate students and scholars in the fields of optimisation, machine learning, and modelling and simulation. See below for relevant opportunities across different career stages.

Prospective Postdoctoral Positions

We are not recruiting any postdoc candidates right now. However, we are always open to applying for projects together or supporting external funding opportunities as a host organisation. If you are interested, please email us a CV and a brief description of your interests and how you see us working together.

Prospective PhD Positions

Currently there are no openings for PhD positions. However, if you are interested, please email us your CV and a description of your interests and fit with our lab. We do not always have funding but we always respond to promising candidates, and maintain an archive of candidates who fit in and can potentially expand our vision.

Prospective Master’s Projects

We host TU Delft and Leiden-Delft-Erasmus master students for their thesis (30-45 credits), or extra coursework in the form of a project worth 15 credits. If you are interested in working with us at the STAR Lab, write to us with your CV and a description of your research interests. Please mention how your interests intersect with the work of the lab. You can find specific projects on TU Delft CS projectforum (search for "starlab"), and previous theses on the TU Delft repository (search for "yorke-smith"). TU Delft BSc students looking for a research or honours opportunity are also welcome to contact us.

Prospective Interns

We cannot host undergraduate interns from outside Leiden University, TU Delft, Erasmus Medical Centre or Erasmus University Rotterdam. We can sometimes host master's interns from Europe under limited conditions. We welcome PhD exchanges, especially through networks of which we are part such as CAIRNE and ELLIS.