Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- SciLifeLab
- KTH Royal Institute of Technology
- Chalmers University of Technology
- Linköping University
- Umeå University
- Lunds universitet
- Chalmers tekniska högskola
- University of Lund
- Karlstad University
- Karolinska Institutet (KI)
- Nature Careers
- Blekinge Institute of Technology
- Stockholms universitet
- Uppsala universitet
- Linnaeus University
- Lulea University of Technology
- Mälardalen University
- Karlstads universitet
- Swedish University of Agricultural Sciences
- Umeå universitet
- Umeå universitet stipendiemodul
- Örebro University
- Linneuniversitetet
- Luleå University of Technology
- University of Gothenburg
- Chalmers Tekniska Högskola AB
- Institutionen för biomedicinsk vetenskap
- Linkopings universitet
- Linköpings universitet
- Lund University
- Malmö universitet
- NORDITA-Nordic Institute for Theoretical Physics
- School of Business, Society and Engineering
- Stockholm University
- 24 more »
- « less
-
Field
-
, TensorFlow, JAX). Demonstrated ability to work in interdisciplinary teams bridging machine learning, neuroscience, and chemistry. Excellent communicative skills and Collaborative abilities Motivation and
-
their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
-
), research is carried out in computer vision, robotics and machine learning. We are now looking for two postdocs in robotics and machine learning and computer vision. The successful candidates is expected
-
Research Infrastructure? No Offer Description The Department of Physics at Chalmers University of Technology invites applications for a postdoc position targeting machine learning in optics. In this position
-
The Department of Physics at Chalmers University of Technology invites applications for a postdoc position targeting machine learning in optics. In this position, you will become part of a
-
to tumour tissue images have improved characterisation of cancer tumours in clinical routine. However, traditional machine learning models require annotated data and are limited in scope, while foundation
-
extensive experience with physics-guided modeling; strong interest in time series machine learning and the ambition to learn are what matter most. The results will support safer automation, fewer failure
-
professional development opportunities and strive to meet each individual’s development and well-being goals as much as possible. As an associate researcher with expertise in the field of machine learning within
-
universities in Machine learning, especially in Deep Learning, with a high concentration of ELLIS (European Laboratory for Learning and Intelligent Systems) researchers, as well as unique labs for field robotics
-
computational, theoretical and/or observational projects, to develop and deploy cutting-edge machine-learning and AI methods for astrophysics and cosmology, enabling precision tests of fundamental physics with