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

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.

Fixed-term contract: 4 jaar.

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.

Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.