Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Chalmers tekniska högskola
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Lunds universitet
- SciLifeLab
- Uppsala universitet
- chalmers tekniska högskola
- Chalmers Tekniska Högskola
- Karolinska Institutet
- Linköping University
- Linköping university
- Linköpings University
- Linköpings universitet
- Sveriges Lantrbruksuniversitet
- Umeå University
- Umeå universitet
- University of Lund
- 8 more »
- « less
-
Field
-
(e.g., power electronics or machine learning applications in power systems). The PhD degree must have been awarded no more than three years prior to the application deadline*. The ideal candidate has
-
analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
-
, Automotive, and Mechanical Engineering, and provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and
-
provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and society, focusing strongly on practical
-
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
-
, through the development of new materials to direct industrial projects generating new inventions. We have a strong learning commitment on all levels from undergraduate to PhD studies where physics meet
-
materials to direct industrial projects generating new inventions. We have a strong learning commitment on all levels from undergraduate to PhD studies where physics meet engineering. The research
-
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
-
related fields. Experience in Machine Learning/AI, mathematical, computational and statistical training are also advantageous. About the employment The employment is a temporary position of two years