PhD position on generative models for discrete data structures (Closed position)

We have an opening for a PhD position. The research target is the development of deep generative models for discrete data structures such as graphs and in particular molecules. We seek to develop generative models capable of conditional generation as well as what can be considered the equivalent of style transfer for discrete structures.

The successful candidate will enrol 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. Starting date 1/September/2022 (negotiable). The position is funded by a Swiss National Science Foundation grant with funding secured for four years.

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 very good 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
- contact details of three referees (do not send reference letters)

We will be accepting applications until the position is assigned.

For any questions please contact Alexandros.Kalousis@hesge.ch