Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
! Education Master's degree (Bac+5) in telecommunications, computer science, or a related field, with an interest in AI, cognitive networks, or connected vehicles. Experience and skills Prior experience with
-
communications at international conferences • 1 PhD thesis supervision and defense • 1 postdoc supervision • Support for obtaining HDR (Habilitation to Direct Research) if not already held SCIENCE
-
Your profile described below? Are you our future colleague? Apply now! Education · PhD degree in Chemical Engineering, Process Engineering, Applied Chemistry or a closely related field, with a
-
train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
-
ability to work in a cooperative, multi-cultural and multi-disciplinary environment. Dynamism, self-organization, autonomy and drive. Interest for computing biology (R programming, image analysis) will be
-
. Interest for computing biology (R programming, image analysis) will be an additional asset. Contact & applications: Applications should be sent to pierre.guermonprez@pasteur.fr ; julie.helft@inserm.fr
-
? Are you our future colleague? Apply now! Required Qualifications Master degree or PhD in Computer Science or related topic in the sectors of Smart Cities, AI/Robotics, Computer Science, Urban Systems
-
Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
the Master’s 2 and the Graduate Programme “Materials Science” option “Innovative materials, advanced technologies and modelling”. These lessons are necessary to study the behaviour of biobased products
-
to obtain funding for PhD students. In parallel, applications to FRM and/or Pasteur-MD-PhD-PPU program will be also encouraged. Opportunities for Interdisciplinary Training: Depending on the candidate’s
-
Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems