Are you interested in interdisciplinary machine learning research? The Amsterdam Machine Learning Lab in collaboration with the Amsterdam ELLIS Unit has two open tenure track positions at the assistant professor level.
Machine learning has become a driving force behind many recent breakthroughs in artificial intelligence. From speech-recognition, image analysis, natural language understanding, machine translation, query and answering systems, protein folding, and even playing GO, deep learning is breaking records. These exciting developments have not gone unnoticed to industry either: Google, Facebook, IBM, Qualcomm, Yahoo, Microsoft, Bosch, Uber and so on all have large teams of researchers working in machine / deep learning.
AMLAB is performing high quality research in fields ranging from probabilistic programming, geometric deep learning, unsupervised and self-supervised learning, causality, reinforcement learning, and more. We study a wide range of applications in astronomy, physics, biology, autonomous driving, medical image analysis etc.
We are inviting applications from excellent candidates in a broad range of topics including:
- probabilistic programming;
- neural approaches to programming;
- induction, combinatorial optimization and reasoning;
- quantum machine learning;
- applications of ML in the physical sciences.
We are committed to offer at least one of the positions to a female candidate in the case of equal qualifications.
What are you going to do?
- You are expected to conduct top level research in machine learning and publish in the top tier conferences and journals such as NeurIPS, ICML, ICLR, JMLR, AISTATS, and UAI;
- 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 will contribute to strengthening the curriculum in machine learning of the Master AI, the Bachelor AI and related programmes such as the Bachelor at the AUC and the Master Information Systems, which all offer ML courses. The teaching load is around 30%;
- you are expected to contribute to valorisation, 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, we expect you to help with the management of the Informatics Institute.
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