Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- SciLifeLab
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Chalmers tekniska högskola
- Uppsala universitet
- Linköping University
- Lunds universitet
- Umeå University
- Blekinge Institute of Technology
- Karolinska Institutet (KI)
- Stockholms universitet
- Linköpings universitet
- Umeå universitet
- University of Lund
- Luleå University of Technology
- chalmers tekniska högskola
- Linkopings universitet
- Mälardalen University
- The University of Gothenburg
- Chalmers Tekniska Högskola
- Chalmers Tekniska Högskola AB
- Department of Chemistry and Molecular Biology, University of Gothenburg
- Institutionen för biomedicinsk vetenskap
- Karlstad University
- Karlstads universitet
- Karolinska Institutet
- Kungliga Tekniska högskolan
- Linköping university
- Linköpings University
- Lulea University of Technology
- Luleå tekniska universitet
- Malmö universitet
- Nature Careers
- School of Business, Society and Engineering
- Sveriges Lantrbruksuniversitet
- University of Gothenburg
- Örebro University
- 27 more »
- « less
-
Field
-
data. Much focus is on large scale analysis based on machine learning, deep learning/AI, as well as handling and analyzing large 3D microscopy data. You will work with shorter and longer projects and
-
-from-motion, and object recognition. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as
-
teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity of further development. The postdoc is expected to collaborate with PhD students in
-
collaboration with Lund University. The candidate is expected to have a strong mathematical background particularly in stochastic modeling, optimization, and reinforcement learning. As a PhD student, you devote
-
for molecular dynamics (MD), slashing computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with
-
machine learning models in simple, standalone devices that are capable of advanced processing. Building on our work on solution-based neuromorphic classifiers (https://doi.org/10.1002/advs.202207023
-
, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
-
strategies: Leveraging traditional and causal machine learning approaches to determine which patients are most likely to benefit from specific therapies. Digital pathology and image-based analyses (starting
-
propagation, electromagnetics, optimization, machine learning, and networking. Strong documented experience in these areas is commendable, particularly by having published your work. Candidates should have an
-
: Analyze spectroscopic and kinetic data, employ statistical and machine learning approaches where relevant, and contribute to manuscripts, presentations, and reports. Collaboration: Work closely with project