AMLAB is seeking a junior faculty in the general field of machine learning methods. The position is broadly defined; we consider any candidate who regularly published in some of the top venues in machine learning, such as Neurips, ICML, ICLR, UAI, AISTATS, JMLR, or TPAMI. Topics of interest are supervised, unsupervised and semi-supervised learning, representation learning, domain adaptation, active learning, reinforcement learning, Bayesian methods, compression and quantization, Bayesian optimization, hybrid generative-discriminative methods, uncertainty quantification etc. We are open to more ‘exotic topics’ such as quantum ML or other physics inspired ML topics as well. We are interested in a candidate with a practical aptitude to build new methods and models and test them or real-world data. We also hope that the candidate has a strong preference to collaborate with other researchers in the natural sciences, medical sciences, social sciences and industry.

What are you going to do?

In this tenure track position you are expected to set up a research group and co-manage and scientifically co-direct the machine learning and deep learning labs in AMLAB. In addition, the you are expected to acquire your own independent funding from sources such as NWO/STW (e.g. VIDI), H2020 (e.g. ERC starting grant) and industry.

In terms of teaching, you are expected to contribute to strengthening the curriculum in machine learning and deep learning of the Bachelor and Master AI and related programs such as the bachelor and master Information Systems, which all offer ML courses. The total teaching load will be around 30%.

You should have a broad interest in machine learning which means that you must be able to teach a wide variety of AI and ML courses in both BSc and MSc.

You are expected to contribute to valorization, both in terms of engaging with the media as well as applying the state-of-the-art research tools to applications in society. UvA spinoffs that bring technology to industry and society are highly encouraged.

Finally, you are expected to help with the management of the Informatics Institute.

• Your research interests should fall within the general area of machine learning;
• a doctorate in Computer Science or a related area;
• a strong track record in research is important, as demonstrated by independent scientific publications in peer reviewed journals, as well as research interest and expertise in the area of machine learning;
• the ability to obtain research funding in a competitive environment and experience in the process of proposal writing;
• a proven track record of teaching and didactic abilities as well as the ability to supervise BSc, MSc and PhD students;
• management skills required for general academic administration, organisation and coordination tasks;
• excellent communication skills;
• an excellent command of English and willingness to learn the Dutch language;
• at least two years of postdoc experience is expected but not strictly necessary.

International research experience is preferred.

Fixed-term contract: five years.

Our offer

We offer you a tenure-track agreement for five years (which is part of a six-year temporary appointment). At the start, we will draw up an agreement with you, specifying the tenure-track requirements for research, teaching and management tasks that need to be fulfilled in order to assess progress after three years and after five years. The requirements in this agreement are negotiable and depend on your experience and scientific profile. Following a positive assessment after five years the appointment will become permanent.

The starting salary will be in accordance with university regulations for academic personnel, and depending on experience and qualifications. It will range from a minimum of €3,637 (scale 10) to a maximum of €5,656 (scale 12) gross per month, based on fulltime (38 hours a week), exclusive 8 % holiday allowance and 8.3 % end-of-year bonus. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable.

Are you curious about our extensive package of secondary employment benefits? Then find out more about working at the Faculty of Science.

University of Amsterdam

With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

Faculty of Science – Informatics Institute

The Faculty of Science has a student body of around 6,500, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The Amsterdam Machine Learning Lab (AMLAB) is led by Prof. Max Welling and also includes Dr Joris Mooij, Dr Herke van Hoof, Dr,  Patrick Forré and Dr Erik Bekkers as well as around 30 PhDs and postdocs. Other groups doing related deep learning research within the Informatics Institute are the Intelligent Sensory Information Systems (ISIS) group (led by Prof. Cees Snoek), the Computer Vision (CV) group led by Prof. Theo Gevers, and the Information and Language Systems (ILPS) group (led by Prof. Maarten de Rijke). Affiliated labs are the Qualcomm-UVA deep learning  & computer vision lab (QUVA) with 12 PhD students and postdocs and the Bosch-UvA DELTA Lab with 10 PhD students and postdocs.