PhD positions: Machine Learning for Imaging and Security
The Stochastic Information Processing Group (SIP) (http://sip.unige.ch), University of Geneva, Switzerland, has two open PhD positions in machine learning.
PROFILE:
- Master degree or an equivalent in one of the following domains: computer science, electrical engineering or mathematics
- Previous experience with machine learning and signal/image processing
- Strong programming skills in Python with some experience in TensorFlow, PyTorch or Keras that will be verified
- Strong verbal and written communication skills in English
- Strong analytical abilities and problem solving/troubleshooting skills more
PhD positions: Machine Learning in participe physics and astro-physics
The Stochastic Information Processing Group (SIP) (http://sip.unige.ch), University of Geneva, Switzerland, has two open PhD positions in machine learning in the scope of Swiss Synergia Project RODEM in partnership with particle physics and astrophysics groups providing data from CERN and several NASA missions.
PROFILE:
- Master degree or an equivalent in one of the following domains: computer science, mathematics or physics
- Previous experience with machine learning and signal/image processing and/or computer vision
- Strong programming skills in Python with some experience in TensorFlow, PyTorch or Keras that will be verified
- Strong verbal and written communication skills in English
Founded in 1559, the University of Geneva is the third largest university in Switzerland by number of students, and ranked second in Switzerland according to the Shanghai Ranking of World Universities 2019.
The city of Geneva is centrally located in Europe, host of numerous international organizations (e.g. UN, WHO, WIPO, WTO, ICRC, CERN), and provides an ideal environment for foreign students and researchers.
CONTACTS:
For further information and applications, please contact
Prof. Slava Voloshynovskiy
University of Geneva
7, route de Drize, CH-1227 Geneva, SWITZERLAND
Phone : +41(22) 379 0158; fax: +41(22)379 0079
E-mail: svolos@unige.ch
