We have an opening for a PhD position. The research target is the development of deep generative models that can incorporate strong domain knowledge within the learning process. Such domain knowledge, typically available in scientific fields, can be encoded in various forms such as equation-based models (e.g. physics and chemistry), simulators (e.g. biomechanical models), and more general black-box programming artifacts (chemoinformatics RDKit). Eventually such models should be considerably more data efficient and offer additional advantages in terms of interpretability.
The successful candidate will enroll as a PhD student in the Computer Science department of the University of Geneva (under the co-direction of Prof. Alexandros Kalousis and Prof. Stephane Marchand-Maillet) and, at the same time, will become a member of the Data Mining and Machine Learning group (http://dmml.ch) at the University of Applied Sciences, Geneva. The position shall be filled in as soon as possible.
We seek strongly motivated candidates prepared to dedicate to high quality research. The candidate should have (or be close to obtaining) a Master's degree or equivalent in computer science, statistics, applied mathematics, electrical engineering or other related field with strong background in machine learning and programming (Pytorch and/or Tensorflow).
If interested, please send the following to alexandros.kalousis@hesge.ch
- academic CV (max 2 pages)
- academic transcripts of BSc and MSc
- one page motivation letter explaining why the candidate is suitable for the position
- 500 word research proposal on one of the topics described above
- contact details of three referees (do not send reference letters)
Deadline for applications: 31/12/2020.
In case of any further questions, please contact alexandros.kalousis@hesge.ch.
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