Sort by
Refine Your Search
-
Listed
-
Employer
- KTH Royal Institute of Technology
- Chalmers University of Technology
- Chalmers tekniska högskola
- Karolinska Institutet (KI)
- Lunds universitet
- Umeå University
- Umeå universitet stipendiemodul
- University of Lund
- Linköpings universitet
- SciLifeLab
- Umeå universitet
- chalmers tekniska högskola
- Karolinska Institutet
- Linköping university
- Linnaeus University
- Linneuniversitetet
- Nature Careers
- Sveriges Lantrbruksuniversitet
- Uppsala universitet
- Örebro University
- 10 more »
- « less
-
Field
-
, obtained within the last three years prior to the application deadline Strong background in machine learning, statistical modeling, and big-data analytics. Experience with infrastructure or transportation
-
of large-scale machine learning models (e.g., LLMs) in a meaningful way, we, therefore, need new scalable methodologies that can efficiently and accurately capture, represent, and reason about uncertainties
-
Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A
-
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
-
consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
-
standards. About the research project The postdoctoral project will focus on precision tests of low-energy strong interactions via the ab initio modeling of open-shell, nuclear many-body systems and Bayesian
-
, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related fields, is a requirement. Experience with computational modeling in metabolomics and metabolic
-
to numerical analysis and optimization, as well as mathematical statistics and machine learning. The centre offers a lively academic environment where colleagues from many parts of the world come together
-
semantic representation models for sign language. Such representations are key to allowing SL to be efficiently processed by large language models (LLMs), and will lead to machine learning models that can
-
imaging technologies. Strong programming skills in at least one scientific programming language. Solid understanding of statistical methods, machine learning, and/or image analysis pipelines. Strong written