Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- SciLifeLab
- Umeå University
- Lulea University of Technology
- Uppsala universitet
- Blekinge Institute of Technology
- Chalmers University of Technology
- Linköpings universitet, ITN
- Luleå University of Technology
- The Swedish University of Agricultural Sciences (SLU)
- Umeå universitet
- 1 more »
- « less
-
Field
-
to benefit from the doctoral-level education they will receive. The applicant should have a strong quantitative background, for example in statistics, mathematics, computer science, or a related field, very
-
departmental duties, up to a maximum of 20 percent of full-time. Your qualifications You have graduated at Master’s level in computer science and engineering, applied mathematics, applied physics, or electrical
-
meritorious if you provide transcripts with documented coursework in algorithms, theory of computing, quantum computing, and discrete mathematics. provide published work on the design or analysis of modes
-
Energy For more information see: www.uu.se/earthsciences The successful candidate will join the research program Air, Water and Landscape Sciences (LUVAL) (https://www.uu.se/en/department/earth-sciences
-
Computer science » Other Engineering » Control engineering Engineering » Systems engineering Engineering » Other Mathematics » Applied mathematics Medical sciences » Other Researcher Profile Recognised Researcher
-
computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or Have completed at least 240
-
engineering physics, nuclear engineering, applied physics, energy engineering, computational science, applied mathematics, statistics, machine learning or another area relevant to the project, or have completed
-
level in computational mathematics and statistics, the applicant must have completed at least 90 ECTS credits within the subject of computational mathematics and statistics (including mathematical
-
Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
-
level in Electrical Engineering, Computer Science, or Applied Mathematics with a minimum of 240 credits, at least 60 of which must be in advanced courses in Electrical Engineering or Applied Mathematics