Adaptivity is a crucial capability of living organisms. Current machine learning systems are not equipped with tools that allow them to adjust to new situations and understand their surroundings (e.g., observed data). For instance, a robot should be able to adapt to new environment or task and assess whether the observed reality is known (i.e., likely events) or it should contact a human operator due to unusual observations (i.e., high uncertainty). Moreover, we claim that uncertainty assessment is crucial for communicating with human beings and for decision making. In this project, we aim at designing new models and learning algorithms by combining multiple machine learning methods and developing new ones. In order to quantify uncertainties, we prefer to use deep generative modeling paradigm and frameworks like Variational Autoencoders and flow-based models. However, we believe that standard learning techniques are insufficient to update models and, therefore, continual learning (a.k.a. life-long learning, continuous learning) should be used. Since this is still an open question how continual learning ought to be formulated, we propose to explore different directions that could include, but are not limited to Bayesian nonparametrics and (Bayesian) model distillation. Moreover, a combination of continual learning and deep generative modeling entails new challenges and new research questions.

• The prospective candidate has a Master’s degree or equivalent in AI, Computer Science, Mathematics, Statistics, Data Science or Physics
• Candidates from other fields are welcome if they can prove their experience in machine learning/deep learning
• A candidate should have a solid background in mathematics and programming (Python), demonstrated by successful completion of associated courses 
• A candidate should have  keen interest in Artificial Intelligence

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 €2,325 per month during the first year and increases to €2,972 per month during the fourth year, based on a full-time employment. The job profile of promovendus: 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. And to be a university where personal education and societal involvement play a leading role. Where people from different disciplines and backgrounds work together on innovations and on generating new knowledge. Our teaching and research embrace the whole spectrum of science – from the humanities, the social sciences and the pure sciences through to the life sciences and the medical sciences.

Vrije Universiteit Amsterdam is home to more than 26,500 students. We employ more than 4,600 individuals. The VU campus is easily accessible, located in the heart of Amsterdam’s Zuidas district, a truly inspiring environment for teaching and research.

Diversity
Diversity is one of our university’s core values. We are an inclusive community, and we believe that diversity and international activities enhance the quality of education and research. We are always looking for people who can enhance diversity on our campus thanks to their background and experience.

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 department, institute, project
The PhD candidate will be part of the Department of Computer Science of the Vrije Universiteit Amsterdam (Computational Intelligence group) in a close partnership with the Institute of Informatics of the University of Amsterdam (Amsterdam Machine Learning Lab). Daily supervision will be performed by Dr. Jakub Tomczak (VU). The promotor will be Prof. A.E. Eiben (VU) and the co-promotor will be Prof. M. Welling (UvA).

About the project
The project is part of the national gravity project on Hybrid Intelligence and will be recruiting 27 PhD or postdoc positions in total. For more information on the project and the other positions, see www.hybrid-intelligence-centre.nl

If you are interested in other projects in addition to this position, you can upload your CV & letter also to: http://bit.ly/HIC-VU thereby applying for "Talentpool for Hybrid Intelligence Centre". Scientists from the HI consortium who do not yet have applicants can select those for their own projects using this “Talentpool system”.