26 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "UCL" uni jobs at SciLifeLab in Sweden
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program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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area, from basic research to large-scale applied research, and close contacts with students through the department’s involvement in engineering and master’s programs. Our research and teaching are
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and autoimmune diseases. Camilla Engblom: https://www.scilifelab.se/researchers/camilla-engblom/ Eduardo Villablanca: https://ki.se/en/research/research-areas-centres-and-networks/research-groups
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Factory Service Hub is operated as a project under the Horizon Europe framework program and will include up to 50 AI experts and other staff working close to academic and industrial users across the EuroHPC
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administrators. Each year, we process more than 60,000 samples and generate over 400 Terabases of data. More about our activities and services can be found at: https://www.uu.se/forskning/snpseq and https
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. Preferred qualifications: Proven experience applying machine (deep) learning to imaging data. Strong programming skills, preferably in Python, and use of version control (Git/GitHub). Knowledge of open-source
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Driven Life. Science (DDLS) research program. We have a national assignment and operate a range of services for life science data and e-infrastructure. We also work with issues about FAIR data and open
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live-cell imaging to join the Advanced Optical Bio-Imaging Laboratory (http://www.testalab.org ) in Stockholm as a Research engineer. The position focuses on the investigation of different labelling
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Do you want to contribute to top quality medical research? Karolinska Institutet (KI) is recruiting researchers as part of the SciLifeLab Fellows program. The successful candidates will join KI and
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of Linköping University’s departments. Your profile determines which department will be relevant. Information about our relevant strong research environments can be found at https://liu.se/en/research/wcmm/ddls