865 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions in Sweden
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- University of Lund
- Umeå University
- Swedish University of Agricultural Sciences
- Lunds universitet
- Linköping University
- Karolinska Institutet (KI)
- SciLifeLab
- Lulea University of Technology
- Uppsala universitet
- KTH Royal Institute of Technology
- Nature Careers
- Umeå universitet
- Sveriges Lantbruksuniversitet
- Umeå universitet stipendiemodul
- Jönköping University
- Stockholms universitet
- University of Borås
- Karlstad University
- Luleå tekniska universitet
- Mälardalen University
- Örebro University
- Blekinge Institute of Technology
- Karlstads universitet
- Linnaeus University
- Luleå University of Technology
- University of Gothenburg
- KTH
- Karolinska Institutet, doctoral positions
- Luleå university of technology
- Linköpings universitet
- Linneuniversitetet
- Academic Europe
- Göteborgs Universitet
- Högskolan Väst
- IFM, Linköping University
- Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg
- Lund University
- SLU
- Stockholm University
- Umea University
- Department of Forest Genetics and Plant Physiology
- EFSA - European Food Safety Authority
- European Magnetism Association EMA
- Faculty of Culture and Society
- Göteborg Universitet
- Göteborgs universitet, Department of Marine Sciences
- Higher Education Institute
- IFM/Linköping University
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg
- Institutionen för akvatiska resurser
- Institutionen för växtskyddsbiologi
- Kungliga Tekniska högskolan
- LInköpings universitet
- Linnéuniversitetet
- Lule university of technology
- Luleå
- Luleå tekniska universitet/Luleå University of Technology
- School of Business and Economics, Linnaeus University
- Swedish University of Agricultural Science
- The Institute of Clinical Sciences
- The Swedish University of Agricultural Sciences (SLU)
- The University of Gothenburg
- Umeå Plant Science Center
- University of Gothenburg, Department of Education, Communication and Learning
- University of Skövde
- 56 more »
- « less
-
Field
-
risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
-
). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
-
materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
-
; designing knowledge-graph-based data models for integrating diverse urban, forest, and market data; developing AI-based forecasting and scenario-simulation pipelines that combine machine learning and
-
tools for the design, analysis and evaluation of socially intelligent systems that aim to collaborate with humans in learning and decision-making tasks, often with the aim of improving health. Visit https
-
world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning for batteries, with
-
with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted. The following experience will strengthen your application: Experience in system identification and machine learning is
-
urban, forest, and market data; developing AI-based forecasting and scenario-simulation pipelines that combine machine learning and simulation methods; and creating visual analytics and human-in-the-loop