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PhD Position Safe Learning for Interconnected Systems

Research / Academic
Delft

The successful applicants will work on algorithms and techniques to make Safe Learning (SL) for Large Interconnected Systems a reality. This is a unique opportunity to develop and test new AI techniques for complex interconnected systems, such as those in future (6G and beyond) communications and in mobile & edge computing platforms.
Safe learning is one of the key research challenges in AI today. The lack of principled and practical SL algorithms prevents the use of AI in many critical application domains, especially those with strict quality-of-service criteria that operate under volatile and unforeseen conditions (e.g., the control of autonomous vehicles). The goal of these positions is to contribute to the development of the next generation of AI tools that are safe (i.e., respect system boundaries and operational requirements), robust against various sources of uncertainty, and prompt in adapting to environmental and mission changes. To this end, we envision using ideas and techniques from (but not limited to) the areas of optimistic learning, fair dynamic learning, robust learning, and continual learning, with applications to 6G and Edge AI resource control and decision-making problems.
The positions are part of a new Marie Curie Training Network called FINALITY, in which TU Delft joins forces with top universities and industries, including INRIA, IMDEA, KTH, the University of Avignon (Project Leader), the Cyprus Institute, Nokia, Telefonica, Ericsson, Orange, and others. The PhD students will have opportunities for internships with other academic and industry partners and will be able to participate in thematic summer schools and workshops organized by the project.     

Requirements:

Candidate Profile: Graduates applying for this position should have the following:

  • Strong motivation to tackle challenging research problems.
  • M.Sc. or equivalent in Mathematics, Computer Science, or Electrical Engineering
  • Strong interest in applied optimization, AI/ML, algorithm design (primary); and communication/computing systems (secondary). Prior research experience and publications are a plus.
  • Excellent academic results (First-class honors or equivalent).
  • Very good command of spoken and written English (TU Delft eligibility criteria apply).

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Salary Benefits:

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Work Hours:

36 - 40 hours per week

Address:

Mekelweg 2