Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Lunds universitet
- Linköping University
- Nature Careers
- Chalmers tekniska högskola
- University of Lund
- Umeå University
- Umeå universitet stipendiemodul
- Sveriges lantbruksuniversitet
- Lulea University of Technology
- Linnaeus University
- Luleå University of Technology
- Mälardalen University
- SciLifeLab
- Swedish University of Agricultural Sciences
- Högskolan Väst
- Jönköping University
- University of Gothenburg
- Uppsala universitet
- Chalmers te
- KTH
- Linneuniversitetet
- Lund University
- Lund university
- Mälardalens universitet
- Umeå universitet
- University of Borås
- 19 more »
- « less
-
Field
-
are looking for The following requirements are mandatory: To qualify for the position of postdoc, you must hold a doctoral degree in computer science, artificial intelligence, machine learning, data science
-
related fields. Experience in Machine Learning/AI, mathematical, computational and statistical training are also advantageous. About the employment The employment is a temporary position of two years
-
electro- and thermocatalysis, in collaboration with PhD students. You will: Synthesize catalysts (thin films or metal nanoparticles). Characterize catalysts using a wide range of advanced techniques
-
systems. The applicant is expected to contribute to ongoing projects and is encouraged to actively develop new lines of research within the field. Qualifications Eligible to apply are individuals with a PhD
-
engineering, mechatronics etc. The PhD degree must be awarded no more than three years prior to the application deadline. Required skillset Analytical understanding of Reinforcement Learning, Dynamics and
-
Landscape Architecture Planning and Management (LAPF), along with collaborators in Norway, The Netherlands, Germany and Estonia. You will be responsible for designing, developing, conducting, and analysing
-
ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
-
interdisciplinary team encompassing two departments at SLU (Plant Protection Biology (VSB) and Landscape Architecture Planning and Management (LAPF), along with collaborators in Norway, The Netherlands, Germany and
-
data reflect real‑world disease phenotypes. Advanced analytics: apply AI and machine‑learning techniques (e.g., graph neural networks, multimodal transformers) to uncover novel biomarkers and generate
-
learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted for experimental evaluation. Work duties The main duties involved in a