PhD: Safe Online Optimization for Time-Varying Systems

Delft University of Technology via AcademicTransfer; Nederland; On-site; EUR 36,000 - 45,000; Full time

Job summary

Delft University of Technology (TU Delft) invites applications for a PhD position in safe learning for control. The project focuses on developing computationally efficient safe learning methods for time-varying optimal control, bridging theory and applications.

Collaboration with TU Eindhoven and NEST partners is expected, with a strong emphasis on safe experimentation and validation. The PhD would join the Delft Center for Systems and Control (DCSC) under Dr.

Qualifications

• MSc degree in Systems and Control, Mathematics, Computer Science or similar field (essential).
• Prior experience with optimization algorithms (essential).
• Prior experience with Bayesian optimization (desirable).
• Prior experience with numerical methods (desirable).
• Strong collaboration, communication and writing skills (essential).

Responsibilities

• Develop safe learning methods for time-varying optimal control problems.
• Validate algorithms experimentally in collaboration with partners.
• Publish results and contribute to the TU Delft teaching and research community.

Skills

Collaborative skills

Communication skills

Technical writing

Education

MSc in Systems & Control

Job description

Delft University of Technology (TU Delft) invites applications for a PhD position in safe learning for control. The project focuses on developing computationally efficient safe learning methods for time-varying optimal control, bridging theory and applications.

Collaboration with TU Eindhoven and NEST partners is expected, with a strong emphasis on safe experimentation and validation. The PhD would join the Delft Center for Systems and Control (DCSC) under Dr.