PhD position in Machine Learning and Computer Vision

Geneva, Geneva, ch
Company: University of Geneva
Category: Educational Instruction and Library Occupations
Published on 2021-06-23 04:10:25

The Stochastic Information Processing Group (SIP) (), University of Geneva, Switzerland, has an open PhD position in machine learning and computer vision.


  • Master’s degree or an equivalent in one of the following domains: computer science, data science, electrical engineering, physics or mathematics
  • Previous experience with machine learning, computer vision 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
  • We offer:

  • Great learning opportunities
  • Flexibility in research subjects
  • Support and guidance to publish papers and attending top international machine learning and image processing events
  • Collaboration with academic and industrial partners
  • Salary: about CHF 50’000 per year
  • The PhD position is funded from the Swiss National Science Foundation with the extension up to 5 years.

    The successful applicants will be involved into a research project related to the development of machine learning and computer vision.

    The project concerns fundamental research on the development of new machine learning methods for universal image processing using recent generative models. Additionally, the project covers the development of new machine learning methods based on variational information bottleneck framework and self-learning. An important component of the project is a close collaboration with industry and access to real data.

    The SIP group has a broad network of international collaboration and has excellent possibilities to organize scientific exchange visits and training. The SIP group has also a close collaboration with CERN in the domain of machine learning and is a part of Swiss SKA initiative.


    As soon as possible


    Applications should include a CV, recommendation letters (if any), diploma with grades, links to your publicly available projects, codes or publications (if any).

    Pre-selected candidates will be invited for a skype/zoom interview.



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