Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- SciLifeLab
- Chalmers University of Technology
- University of Lund
- Linköping University
- Umeå University
- Nature Careers
- Blekinge Institute of Technology
- Lulea University of Technology
- Karlstad University
- Swedish University of Agricultural Sciences
- ;
- Mälardalen University
- WORLD MARITIME UNIVERSITY (WMU)
- 3 more »
- « less
-
Field
-
fusion to address key environmental challenges. Strategically positioned to impact Earth observation science, we collaborate on satellite development, NewSpace technologies, and apply machine learning
-
to learn Swedish, to facilitate teaching and research collaboration. Chalmers offers Swedish courses. Mandatory A PhD degree in a relevant field of research, awarded no more than three years prior
-
at the intersection of numerical analysis and scientific machine learning, focusing on the development of reliable, physics-aware AI frameworks. The aim is to build a mathematically grounded approach for approximating
-
and/or functional imaging or application of computational modeling, machine learning and AI to understand cellular function. At least five years’ experience working within the university system, another
-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
-
the postdoctoral appointment’s nature as a career-development position for junior researchers, we are looking for candidates who have completed their PhD no more than three years before the application deadline
-
humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in this context
-
machine learning techniques into a modern AI planning system. The project will involve both theoretical and experimental work As a PhD student, you devote most of your time to doctoral studies and the
-
Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
-
Injection Systems (CIS) — natural protein machines used by bacteria to deliver molecular cargo. The group's mission is to understand the structure, function, and application of CIS for use in both