Postdoc (Meta-)Learning to Give Feedback in Interactive Learning

Postdoc (Meta-)Learning to Give Feedback in Interactive Learning

Published Deadline Location
8 Jul 2 Sep Delft

Job description

Why build AI systems that replace people if we can build AI systems that collaborate with people? Hybrid Intelligence is the combination of human and machine intelligence, expanding human intellect instead of replacing it. Our goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the center, changing the course of the ongoing AI revolution.

The project will be recruiting 15 PhD or postdoc positions in total. For more information on the project see www.hybrid-intelligence-centre.nl.

At Delft University of Technology we are looking for a postdoc who wants to push machine learning beyond traditional settings that assume a fixed dataset. Specifically, in this project we will investigate interactive learning settings in which two or more learners interact by giving each other feedback to reach an outcome that is desirable from a system designers perspective. The goal is to better understand how to structure interactions to effectively progress to the desirable outcome state, and to develop practical learning techniques and algorithms that exploit these generated insights.

This postdoc position is part of the Hybrid Intelligence project and the successful candidate will be supervised by Dr. Frans Oliehoek (TU Delft) and Dr. Herke van Hoof (University of Amsterdam).

If you want to be also considered for one of our other PhD positions, then also upload your documents to our Hybrid Intelligence talent pool.

Your information will then be shared among the researchers in the consortium, and you may be approached for one of the other positions listed on www.hybrid-intelligence-centre.nl/jobs.

Department
The department of Intelligent Systems (INSY) conceptualizes computer science methodologies to sense, abstract, learn, reason, elicitate and adapt data and their meaning in ways that respect human values in order to increase human effectiveness in well-being and social innovation. At the heart of the department is therefore the research and teaching in computer science theory, algorithms and solutions for information processing systems that support humans (e.g. robotics), new products (e.g. internet services), and science (e.g. biology)

The Interactive Intelligence group focuses on interaction of users with intelligent systems. In particular we have a strong track record on the development of smart interactive agents.  Such agents possess capabilities including learning, reasoning, social skills, emotions, and norms and can interact with humans. These agents typically function as coach, artificial actor, or companion, and are used in a wide variety of applications including therapy, health and entertainment.  

The Hybrid Intelligence Centre is a collaboration of top AI researchers from the VU Amsterdam, the University of Amsterdam, the TU Delft, and the Universities of Groningen, Leiden, and Utrecht, in areas such as machine learning, knowledge representation, natural language understanding & generation, information retrieval, multi-agent systems,  psychology, multimodal interaction, social robotics, AI & law and ethics of technology. The HI centre will create a national and international focus point for research on all aspects of Hybrid Intelligent systems.

Specifications

Delft University of Technology (TU Delft)

Requirements

We are looking for a curiosity-driven researcher that is motivated to push the boundaries of machine learning in interactive settings. We expect that the project will consist both of theoretical parts (e.g., proving theorems) and empirical parts (e.g., running simulations, and analyzing the results). Depending on the skills and aptitude of the candidate the research could focus more on the former or the latter.

Strict requirements:

  • a PhD degree in AI or closely related topics in computer science, math, or physics.

Other desiderata:

  • thorough knowledge of general area of reinforcement learning, decision making under uncertainty, and/or other forms of interactive machine learning such as generative adversarial networks, or online learning.
  • track record with international publications
  • good coding skills and experience in contemporary machine learning framework (e.g., Tensorflow, Pytorch)
  • fluent in English
  • self-motivated
  • team player: willing to initiate collaborations with other partners in the project.    

Conditions of employment

Fixed-term contract: 3 years.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, a discount 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. An International Children's Centre offers childcare and there is an international primary school.

Employer

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! 

Department

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.

Additional information

For information about this vacancy or the selection procedure, you can contact Dr. Frans Oliehoek, Associate Professor, who will be the primary supervisor for this position, email: f.a.oliehoek@tudelft.nl.

Specifications

  • Postdoc
  • Engineering
  • 24—40 hours per week
  • €2790—€4402 per month
  • Doctorate
  • TUD00317

Employer

Delft University of Technology (TU Delft)

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Location

Mekelweg 2, 2628 CD, Delft

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Application procedure

To apply, please email a detailed CV with publication list, a motivation letter, a research statement and contact details of 2-3 references by September 1, 2020 to Ms. A.Lacroix, HR-Advisor, vacancies-eemcs@tudelft.nl mentioning vacancy TUD00317.

A pre-employment screening can be part of the application procedure.

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Application procedure

Application procedure

To apply, please email a detailed CV with publication list, a motivation letter, a research statement and contact details of 2-3 references by September 1, 2020 to Ms. A.Lacroix, HR-Advisor, vacancies-eemcs@tudelft.nl mentioning vacancy TUD00317.

A pre-employment screening can be part of the application procedure.

Make sure to apply no later than 2 Sep 2020 1:59 (Europe/Amsterdam).