PhD in Probabilistic Machine Learning

The Uncertainty in Artificial Intelligence (UAI) group is a growing group embedded in the Data and AI (DAI) cluster at the Eindhoven University of Technology (https://dai.win.tue.nl). In the DAI cluster, we aim at developing foundations of AI for the present and the future. This includes the design of new AI methods, development of AI algorithms, and tools with a view at expanding the reach of AI and its generalization abilities. In particular, we study foundational issues of robustness, safety, trust, reliability, tractability, scalability, interpretability, and explainability of AI.

The UAI group is looking for a highly motivated and skilled PhD candidate to work in the area of

probabilistic machine learning. The position is fully funded for a term of four years. The research direction will be determined together with the successful candidate and in line with the NWO Perspectief Project Personalised Care in Oncology (www.personalisedcareinoncology.nl). The research topics may include, but are not restricted to:

• Probabilistic graphical models (Markov, Bayesian, credal networks)
• Causality: Theory and application
• Cautious AI, including imprecise probabilities
• Robust stochastic processes
• Tractable models and decision-making
• Online/continual learning with evolving data

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.