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 knowldege, 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 myself 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.