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  3. PhD Position in Formal Methods for Learned Systems

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PhD Position in Formal Methods for Learned Systems

Challenge: Monitoring of human-in-the-loop learned systems.
Change:     Synergy between formal methods and learning.
Impact:      Reliable deployment of AI in the real world.

ongeveer 2 maanden geleden

Arbeidsvoorwaarden

Standplaats:
Mekelweg, Delft, Zuid-Holland
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 - 40 uur
Salarisindicatie:
€ 2434 - € 3111 per maand
Opleidingsniveau:
WO

Functieomschrijving

The main difference between most modern learned systems and traditional automation is that behavior is not programmed, but derived from examples. When using such systems in practice we need to be able to identify when the system may not be doing what we want. The challenge this project addresses is to support experts in monitoring learned systems, so that they can step in to prevent AI systems making decisions that are discriminating, dangerous or simply wrong.

We consider human feedback to be essential for achieving reliability of learned systems in the real world. We believe in the hidden potential of the synergies between formal and learning-based methods. You will conduct both theoretical and empirical research on monitoring learned systems. You can choose to primarily focus on one of the aspects or their intersection. We envision the project to have both significant scientific and practical impact, across areas that use learning for automation.

You will be part of the Algorithmics Group in the Department of Software Technology of the Faculty of Electrical Engineering, Mathematics and Computer Science. In the Algorithmics group, we aim to design, and understand fundamental properties of, planning and coordination algorithms for intelligent decision making in real world applications. As the member of the group, you will reinforce and extend the group's research activities in the emergent interdisciplinary field combining formal methods and machine learning. Algorithmics group has a long-standing track record in the area of artificial intelligence. Our research output is supported by several awards and by numerous conference papers at IJCAI, AAAI, AAMAS, ECAI, as well as TACAS, CPSWeek, ATVA. In addition, you will have an opportunity to collaborate with the Interactive Intelligence Group internationally recognized for their research on socially interactive agents

Functie-eisen

To be the successful candidate, you should

  • have a Master’s degree in computer science, information/computer/software engineering, mathematics or closely related studies,
  • have firm mathematical foundations in control/formal methods/optimization,
  • have prior experience with deep learning and statistical analysis,
  • have strong programming skills,
  • are proficient in written and spoken English,
  • are a proactive individual excited for scientific research.

Conditions

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2434 per month in the first year to € 3111 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Additional information

For more information about this vacancy, please contact Dr. Anna Lukina, email: a.lukina-1@tudelft.nl, who will be the supervisor for this position.

For information about the application procedure, please contact Sophie den Hartog, Secretary of the Algorithmics Group, s.c.denhartog@tudelft.nl.