You will conduct high quality research with several robotic platforms between the Social AI Group (https://socialai.nl/) and the Computational Group (https://cs.vu.nl/ci/). You will mainly be developing algorithms for social robot learning from human teachers.

Programming interactive robot behavior in socially situated contexts is difficult, time-consuming, and often not generalizable. For these reasons, human teachers can play a valuable role in optimizing robot behavior through interaction. Existing research approaches have allowed both expert and non-expert users to interactively teach robots a variety of tasks according to their own preferences and using a diverse set of communication and teaching modalities. However, most existing methods assume that the underlying human preferences are static and do not change throughout the teaching process. In practice, it has been shown that human preferences are often shaped by the interaction itself.

Using this observation as a starting point, this project aims at leveraging the dynamic nature of human preferences in teaching contexts to allow a robot to actively influence teacher preferences during the interaction. We hypothesize that such an approach could not only increase the quality of interaction, but also potentially increase learning performance by allowing teachers to explore solutions that they may have not initially foreseen. 

This project will contribute to an expanded and richer set of tools that will allow human teachers to flexibly transfer knowledge and skills to robots while at the same time learning about their own preferences. We expect these contributions to be not only of direct relevance to human-robot interaction, but also potentially to other human-in-the-loop domains such as general supervised learning, recommender systems, and technology-assisted design and prototyping.
Your duties

• Analyzing the literature on relevant topics in the area of interactive machine learning and human modeling
• Developing novel algorithms for human-interactive learning with various (humanoid and non-humanoid) robotic platforms
• Running controlled and exploratory user studies to inform and evaluate these algorithms
• Contributing to the group’s infrastructure, including the Social Interaction Cloud https://socialrobotics.atlassian.net/wiki/spaces/CBSR/overview

• Master’s degree or equivalent in a computing related field (computer science, artificial intelligence, engineering, robotics, human-computer interaction, cognitive science, etc.)
• Strong motivation for complex real-world problem solving and a multi-disciplinary approach to research
• Solid programming skills (e.g., Python, C++, Linux, ROS)
• The ability to work as part of a team alongside researchers with diverse perspectives
• Experience with user studies and statistical testing is a plus but not required

Candidates with exceptional relevant skills not listed above may be considered even if they do not fit one of the requirements.

Fixed-term contract: 1 year.

A challenging position in a socially involved organization. The salary will be in accordance with university regulations for academic personnel and amounts €2,395 (PhD) per month during the first year and increases to €3,061 (PhD) per month during the fourth year, based on a full-time employment. The job profile: PhD student, is based on the university job ranking system and is vacant for at least 1 FTE.

The appointment will initially be for 1 year. After a satisfactory evaluation of the initial appointment, the contract will be extended for a total duration of 4 years.
Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• a maximum of 41 days of annual leave based on full-time employment
• 8% holiday allowance and 8.3% end-of-year bonus
• solid pension scheme (ABP)
• contribution to commuting expenses
• optional model for designing a personalized benefits package

The ambition of Vrije Universiteit Amsterdam is clear: to contribute to a better world through outstanding education and ground-breaking research. We strive to be a university where personal development and commitment to society play a leading role. A university where people from different disciplines and backgrounds collaborate to achieve innovations and to generate new knowledge. Our teaching and research encompass the entire spectrum of academic endeavor – from the humanities, the social sciences and the natural sciences through to the life sciences and the medical sciences.

Vrije Universiteit Amsterdam is home to more than 26,000 students. We employ over 4,600 individuals. The VU campus is easily accessible and located in the heart of Amsterdam’s Zuidas district, a truly inspiring environment for teaching and research.

Diversity
We are an inclusive university community. Diversity is one of our most important values. We believe that engaging in international activities and welcoming students and staff from a wide variety of backgrounds enhances the quality of our education and research. We are always looking for people who can enrich our world with their own unique perspectives and experiences.

The Faculty of Science
The Faculty of Science inspires researchers and students to find sustainable solutions for complex societal issues. From forest fires to big data, from obesity to medicines and from molecules to the moon: our teaching and research programmes cover the full spectrum of the natural sciences. We share knowledge and experience with leading research institutes and industries, both here in the Netherlands and abroad.

Working at the Faculty of Science means working with students, PhD candidates and researchers, all with a clear focus on their field and a broad view of the world. We employ more than 1,250 staff members, and we are home to around 6,000 students.
About the research group
The Social AI and Computational Intelligence Group are embedded within the Computer Science Department. The Social AI group (https://socialai.nl/) aims to research and develop smarter digital companions in order to improve the way humans and machines understand and interact with each other. The Computational Intelligence Group  (https://cs.vu.nl/ci/) researches fundamental issues about how to design, use, and understand intelligent systems made up by autonomous machines that can self-organise, evolve, and learn.