PhD in Safe Planning and Decision-Making under Uncertainty for Long-Horizon Robot Autonomy

Original title: PhD Position: Safe Planning and Decision-Making under Uncertainty for Long-Horizon Robot Autonomy

• An MSc degree in Systems and Control, Robotics, Applied Mathematics, or a closely related field.
• A strong interest in safe planning and decision-making for robots, at the intersection of planning, control, and learning.
• A passion for rigorous, theoretically grounded research, combined with an eagerness to validate ideas in simulation and on real robots.
• Strong analytical and mathematical skills, in particular in optimization, probability and statistics, and dynamical systems.
• Excellent communication skills and proficiency in English (written and verbal), as required for academic publication and international collaboration.
• Hands-on experience implementing optimization-based planners or controllers (e.g., model predictive control with acados or CasADi) in C++ or Python.
• Safe or robust control and planning under uncertainty.
• Learned dynamics or prediction models, model-based reinforcement learning.
• Uncertainty quantification, probabilistic or Bayesian modeling, state estimation.
• Long-horizon or hierarchical planning, prediction of human or multi-agent behavior.
• Real-robot deployment with ROS or ROS 2.
• A letter of motivation explaining why you are the right candidate for this project
• An updated cv
• Exam transcipts from your Bachelor and Master
• A copy of your MSc thesis, or draft MSc thesis (or a link to access it)
• #EUfunded This is an EU funded project, named OPERA, with project number 101298363, within program HORIZON/HORIZON-CL4-2025-04-DIGITAL-EMERGING-07
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.