Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- KTH Royal Institute of Technology
- Chalmers University of Technology
- Chalmers tekniska högskola
- Lunds universitet
- Umeå University
- Karolinska Institutet (KI)
- Umeå universitet
- Umeå universitet stipendiemodul
- University of Lund
- Linköpings universitet
- Nature Careers
- SciLifeLab
- Uppsala universitet
- chalmers tekniska högskola
- Örebro University
- Chalmers Tekniska Högskola
- Karolinska Institutet
- Linköping University
- Linköping university
- Linköpings University
- Linnaeus University
- Linneuniversitetet
- Lund University
- Sveriges Lantrbruksuniversitet
- 14 more »
- « less
-
Field
-
funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in developing new image analysis and machine learning methods
-
science. You will be part of a dynamic research group with expertise in Earth Observation, geoinformatics, and machine learning, offering an excellent environment for advancing your research and building
-
strategies: Leveraging traditional and causal machine learning approaches to determine which patients are most likely to benefit from specific therapies. Digital pathology and image-based analyses (starting
-
: detection of objects and relations between objects, and use of these relations to infer new knowledge (i.e. reasoning); (ii) explore object affordances, learn the consequences of the actions carried out and
-
and refined our pioneering AI-driven methods. This project focuses on improving protein structure prediction, design, quality assessment, and dynamics using innovative machine learning techniques. You
-
design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments
-
groups working towards a common goal. For this postdoc project, we seek a dynamic and motivated candidate with an interest in computational electromagnetism, inverse design, and/or machine learning in
-
: What are efficient machine learning strategies to identify large ensembles of nanoparticles in tomograms (i.e., to identify nanoparticles on irregular 2D surfaces in 3D space)? What are appropriate
-
intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
-
measurement and control platform for optimal island operation of Chalmers’ wind-battery system. Machine learning-based forecasting tools for renewable production using limited local measurement data