Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Umeå University
- Linköping University
- Lunds universitet
- Uppsala universitet
- Chalmers University of Technology
- Swedish University of Agricultural Sciences
- Stockholms universitet
- Sveriges lantbruksuniversitet
- SciLifeLab
- University of Lund
- Luleå University of Technology
- Mälardalen University
- Umeå universitet
- Jönköping University
- Linköpings universitet
- Nature Careers
- University of Gothenburg
- Lulea University of Technology
- Chalmers Tekniska Högskola
- Chalmers University of Techonology
- Chalmers tekniska högskola
- Fureho AB
- Institutionen för biomedicinsk vetenskap
- KTH Royal Institute of Technology
- Karolinska Institutet, doctoral positions
- Linkopings universitet
- Linnaeus University
- Malmö universitet
- Mälardalens universitet
- School of Business, Society and Engineering
- Stockholm University
- The University of Gothenburg
- 22 more »
- « less
-
Field
-
the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
-
application! We are now looking for a PhD student in Integrated Circuits and Systems, at the Department of Electrical Engineering (ISY). Your work assignments The objectives for this position are to develop
-
chemistry, biochemistry and organic chemistry. More than 100 people, including around 45 PhD students, work at the department. New employees and students are recruited from all over the world and English is
-
, including around 45 PhD students, work at the department. New employees and students are recruited from all over the world and English is the main working language. The department is located at the Biomedical
-
. Funding is provided for doctoral candidates from both inside and outside Europe to carry out individual project work in a European country other than their own. The training network “SPACER” is made up
-
Advanced Grant to determine the optimal combination of epitopes that elicits the highest level of protection. Within the research group, we value a positive work environment built on respect and
-
affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from
-
, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
-
. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
-
decision-support tools for energy-aware planning, predictive maintenance, and resource optimization, -use robotics, autonomous systems, IEC 61499, and digital twins to design and evaluate distributed control