896 machine-learning "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
- Lunds universitet
- Swedish University of Agricultural Sciences
- Umeå University
- Linköping University
- SciLifeLab
- Lulea University of Technology
- Nature Careers
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Uppsala universitet
- Umeå universitet
- Jönköping University
- Stockholms universitet
- Umeå universitet stipendiemodul
- University of Borås
- Mälardalen University
- Sveriges Lantbruksuniversitet
- Blekinge Institute of Technology
- Karlstad University
- Linnaeus University
- Luleå University of Technology
- Luleå tekniska universitet
- University of Gothenburg
- KTH
- Örebro University
- Karolinska Institutet, doctoral positions
- Lund University
- Luleå university of technology
- Malmö university
- Mid Sweden University
- Göteborgs Universitet
- Karlstads universitet
- Linköpings universitet
- Linneuniversitetet
- Academic Europe
- Högskolan Väst
- IFM, Linköping University
- Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg
- Linnéuniversitetet
- SLU
- Stockholm University
- The Faculty of Education and Society
- Umea University
- Department of Forest Genetics and Plant Physiology
- Faculty of Culture and Society
- Faculty of Health and Society
- Faculty of culture and society
- Göteborg Universitet
- Göteborgs Universitet, Institution för kemi och molekylärbiologi
- Göteborgs universitet, Department of Marine Sciences
- Higher Education Institute
- IFM/Linköping University
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg
- Institutionen för kemi och molekylärbiologi
- Kungliga Tekniska högskolan
- LInköpings universitet
- Lule university of technology
- Luleå
- Mittuniversitetet
- Sveriges Lantrbuksuniversitet
- The Faculty of Health and Society
- The Faculty of Odontology
- The Faculty of Technology and Society
- The Swedish University of Agricultural Sciences (SLU)
- Umeå Plant Science Center
- University of Gothenburg, Department of Education, Communication and Learning
- 58 more »
- « less
-
Field
-
research - Analytical skill - Other documented knowledge or experience that may be relevant to doctoral studies in the subject. All applicants will be informed when the recruitment is completed. https
-
education to enable regions to expand quickly and sustainably. In fact, the future is made here. Description of work You will be working in the laboratory of Marta Bally (https://ballylab.com/ ), in close
-
at https://nbis.se. Duties We are seeking a candidate who wants to help enable life science research in Sweden that goes beyond what is achievable by individual researchers, a single university, or a single
-
Computational Mathematics) and some departmental duties, mainly teaching for basic level courses. Teaching can be performed in English, and there is support for learning the Swedish language if desired
-
aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn
-
. The department will provide support with language learning. Eligibility The applicant must meet the following qualification requirements: PhD or equivalent academic qualifications research expertise in
-
and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed
-
today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
-
independent courses at an advanced level in occupational therapy and can award an advanced level degree in occupational therapy. The Occupational Therapy program (https://www.gu.se/studera/hitta-utbildning
-
computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation