Sort by
Refine Your Search
-
Listed
-
Employer
- KTH Royal Institute of Technology
- Chalmers University of Technology
- University of Lund
- Lunds universitet
- SciLifeLab
- Linköping University
- Lulea University of Technology
- Sveriges Lantbruksuniversitet
- Jönköping University
- KTH
- Mälardalen University
- Swedish University of Agricultural Sciences
- Umeå University
- Umeå universitet
- Umeå universitet stipendiemodul
- Göteborgs universitet, Department of Marine Sciences
- Högskolan Väst
- IFM, Linköping University
- IFM/Linköping University
- Karolinska Institutet (KI)
- Linköpings universitet
- Luleå University of Technology
- Luleå tekniska universitet
- Lund University
- Nature Careers
- Uppsala universitet
- 16 more »
- « less
-
Field
-
intelligence - Data-driven and learning-based control - Decentralized decision-making and distributed optimization - Belief-space and uncertainty-aware planning - Neuro-symbolic and context-aware reasoning
-
learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. The postdoctoral position is proposed around the following project
-
in clinically relevant environments. Key work assignments include: Design, fabrication, and optimization of high-performance plasmonic nanostructures and SERS substrates for sensing in complex
-
on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
-
-throughput computational screening methods for alloy design, experimental alloy production (casting and/or AM), testing and characterisation of the thermo-physical and mechanical properties of the designed
-
travel combustion engines. The research involves computational thermodynamics (CALPHAD), high-throughput computational screening methods for alloy design, experimental alloy production (casting and/or AM
-
on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
-
, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also committed to building a safe and positive
-
the project Con-TEki investigates the role of transposable elements (TEs) as drivers of regulatory innovation in conifers (Norway spruce and Scots pine), contrasting outcomes with an angiosperm (aspen
-
innovation in conifers (Norway spruce and Scots pine), contrasting outcomes with an angiosperm (aspen). The project combines genomic, epigenomic and 3D chromatin profiling (ATAC-Seq, easySHARE-Seq, ChIP-Seq