PHD Position Efficient Online Optimization for Time

Logo of EURAXESS Delft University of Technology (TU Delft) Engineering » Control engineering First Stage Researcher (R1) 23 Nov 2026 - 22:59 (UTC) Country Netherlands Type of Contract Permanent Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description How to avoid learning too much - safe and efficient learning for control Job description Inefficient operation of industrial systems, electricity production, and heating systems in buildings is currently responsible for over 50% of overall greenhouse gases emissions. Improving energy efficiency of energy-intensive sectors by implementing advanced control systems has the potential to both improve efficiency and reduce the costs, all while continuing to meet safety requirements. The flexibility of safe and adaptive learning control methods makes them crucial for safety-critical applications. A key difficulty in these learning-based approaches lies in the fact that the algorithm must simultaneously learn the model and guarantee safety. This dual requirement significantly impacts the computational cost of the learning algorithm, particularly in situations where the optimal decision evolves over time. We now aim to develop computationally efficient safe learning methods for time-varying optimal control problems. Existing safe learning algorithms usually assume that they have unlimited access to the experiments and thus unlimited new data. Approaches using limited data sets have been restricted to Bayesian optimization without safety constraints. Moreover, the algorithms typically rely on the repetitive nature of the experiments, for instance in robotics or precision manufacturing. The unlimited data combined with repetitiveness limit the applicability of safe learning algorithms in problems evolvi...

⚑ 岗位信息收录自公开招聘页（公开招聘平台），以雇主官网为准