Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Code 9519 Employee Class Grad/Prof Student Position Add to My Favorite Jobs Email this Job About the Job This person will act as a teaching assistant in the course NSC 5661 Systems Neuroscience. This job
-
of Economics and Business The Faculty of Economics and Business offers an inspiring study and working environment for students and employees. International accreditation enables the Faculty to assess performance
-
this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
-
this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
-
this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
-
, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
-
The Groningen Institute for Evolutionary Life Sciences (GELIFES - https://www.rug.nl/research/gelifes/ ) offers a 4-year M20 Program funded PhD position for a project on “Multi-dimensional
-
the above ‘Apply’ button. Under ‘campus’ please select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero’. Please quote the advertised reference number *LU-EnerHy-2025-1* under
-
will be employed at Doctoral level (PhD) at the Department of Computer Science of the University of Luxembourg (UL). She/he will be supervised by Prof. Dr. Christoph Schommer and is expected to conduct
-
to shape a more inclusive, sustainable, and innovative future. The Brussels Institute for Statistics and Information Science (BISI) is a multidisciplinary research group within the VUB, focusing on data