Time-scale aware analysis and control of hybrid networked systems

Time-scale aware analysis and control of hybrid networked systems

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Project

Profile

The ideal candidate holds a master’s degree in engineering (control, electrical, mechanical, mathematical) or mathematics (applied, computational), with a strong interest in systems and control theory. Applicants whose first language is not English must provide an official language test report.

Offer

  • A fully funded PhD position in an international context for four years, as part of the Global PhD Fellowship Program at KU Leuven, including a yearly benchmark fee
  • A competitive salary (tax-free fellowship starting from approximately 2500 EUR/month), along with social and medical insurance
  • Additional benefits such as a KU Leuven bike, access to university sports facilities, and priority access to university daycare centers
  • Flexible working hours and home office arrangements
  • A diverse and multidisciplinary research team
  • Collaborations with international research labs and experts
  • Support for professional career development, including a wide range of technical and transferable skill courses offered by the Arenberg Doctoral School of KU Leuven and the MADIS doctoral school of the Université de Lille

Interested?




KU Leuven is committed to fostering an inclusive, respectful, and socially safe environment. We value diversity among individuals and groups as a strength. Open dialogue and diverse perspectives are crucial for an ambitious research and educational environment. In line with our commitment to equal opportunity, we acknowledge the impacts of historical inequalities. We do not tolerate discrimination based on gender identity and expression, sexual orientation, age, ethnic or national background, skin color, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or the support we offer, please contact us at this email address.

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Job Overview

Time-scale aware analysis and control of hybrid networked systems