862 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" 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
- Karolinska Institutet (KI)
- Lulea University of Technology
- Umeå universitet
- KTH Royal Institute of Technology
- Nature Careers
- Uppsala universitet
- Jönköping University
- Umeå universitet stipendiemodul
- University of Borås
- Stockholms universitet
- Sveriges Lantbruksuniversitet
- Mälardalen University
- Karlstad University
- Luleå tekniska universitet
- Örebro University
- Blekinge Institute of Technology
- Linnaeus University
- Luleå University of Technology
- University of Gothenburg
- KTH
- Karlstads universitet
- Karolinska Institutet, doctoral positions
- Luleå university of technology
- Linköpings universitet
- Linneuniversitetet
- Lund University
- Academic Europe
- Göteborgs Universitet
- Högskolan Väst
- IFM, Linköping University
- Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg
- 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
- The Swedish University of Agricultural Sciences (SLU)
- Umeå Plant Science Center
- University of Gothenburg, Department of Education, Communication and Learning
- University of Skövde
- 53 more »
- « less
-
Field
-
for three weeks of training in higher education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity of further development. Detailed
-
for three weeks of training in higher education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity for further development
-
machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
-
a strong constellation of both traditional applied biostatistics and expertise in artificial intelligence and machine learning, which is undergoing rapid development. The clinical activities
-
projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
-
) and Machine Learning/NLP (Natural Language Processing) to capture both the network embeddedness and the qualitative B2B relationship features of supply chains. The project identifies key bottlenecks
-
well as in urban areas. See also: https://www.slu.se/en/about-slu/organisation/departments/ecology/ About the position The researcher will work in the field (in southern Sweden), with statistical analyses, and
-
initiative started in 2018 with the purpose of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer). For the research on quantum optics with
-
highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
-
-energy devices. Using state-of-the-art electronic-structure calculations and machine learning methods, you will model these effects and contribute to the design of improved semiconductors for solar cells