Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- KTH Royal Institute of Technology
- Lunds universitet
- University of Lund
- Umeå University
- SciLifeLab
- Uppsala universitet
- Chalmers University of Technology
- Linköping University
- Swedish University of Agricultural Sciences
- Chalmers tekniska högskola
- Umeå universitet
- Örebro University
- Linköpings universitet
- Luleå University of Technology
- Sveriges Lantbruksuniversitet
- Blekinge Institute of Technology
- Lulea University of Technology
- Stockholms universitet
- University of Borås
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Karolinska Institutet (KI)
- Linkopings universitet
- Linköpings University
- Malmö universitet
- Nature Careers
- Sveriges lantbruksuniversitet
- 16 more »
- « less
-
Field
-
develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates
-
to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
-
to disease development experience in relevant evolutionary biology and phylogenetic sequence analysis publications in peer-reviewed scientific journals great importance will be placed on personal qualities
-
on literature from mathematics, computer science, robotics, and game theory. Join a growing research group developing state-of-the-art algorithms for agentic decision making. About us The Department of
-
of molecular dynamics algorithms in GROMACS. The main focus will be on mixed precision techniques as part of the GANANA EU-India HPC partnership. This R&D work will involve: Design and development of mixed
-
want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international
-
experience in radar research, developing signal processing algorithms for long-range ultra-broadband Synthetic Aperture Radar systems and short-range FMCW systems. In recent years, breakthroughs in
-
series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
-
at the Faculty of Engineering and contribute to cutting-edge research in radar systems. The radar group at BTH has extensive experience in radar research, developing signal processing algorithms for long-range
-
. Additional qualifications Experience from providing support in image analysis to other researchers is meriting. Especially meriting is proficiency in using and developing algorithms and analysis pipelines