Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Chalmers tekniska högskola
- University of Lund
- KTH Royal Institute of Technology
- Lunds universitet
- Nature Careers
- SciLifeLab
- Umeå University
- Chalmers Tekniska Högskola
- Karolinska Institutet (KI)
- Linköping university
- Linköpings University
- Sveriges Lantrbruksuniversitet
- Uppsala universitet
- chalmers tekniska högskola
- 5 more »
- « less
-
Field
-
description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
-
to the development of the research milieu. Requirements PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, machine learning, artificial intelligence, data science
-
experience with machine learning techniques in general and neural networks in particular will be highly beneficial. About the employment The employment is a temporary position of 2 years according to central
-
using genetic data from family-based studies as well as -omics data for integrative deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative
-
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
-
deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative research may include but is not limited to software tool dissemination, biology discovery, and
-
(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
-
, Automotive, and Mechanical Engineering, and provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and
-
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
-
provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and society, focusing strongly on practical