105 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" Postdoctoral positions in Sweden
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and in vivo model systems, applying multiple omics methods. You will be working with clinical samples, method development and several molecular biology techniques, especially PCR and sequencing as
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intended support design decisions related to manufacturing and process parameter selections; known to influence the material microstructure. Duties: The post doc will develop and apply computational methods
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, decentralization and mission execution. The RAI team has a strong European participation in multiple R&D&I projects, while RAI was also participating in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA
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develop new quantitative tools to study human tissue in a clinically relevant context. Gothenburg is quickly becoming a hub for life sciences in the Nordics, with a strong focus on research and innovation
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Description The lab of Kristine Steen Jensen is looking for a highly motivated and self-driven postdoctoral research-candidate for the development of systems for producing proteins with posttranslational
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for strategic development: materials research, integration of batteries with power electronics, and safe energy storage. This position is associated with the COMPEL platform located at the Centre for Analysis and
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Landscape Architecture Planning and Management (LAPF), along with collaborators in Norway, The Netherlands, Germany and Estonia. You will be responsible for designing, developing, conducting, and analysing
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Estonia. You will be responsible for designing, developing, conducting, and analysing experiments, which will include small scale field and greenhouse trials of cover crops and potato as well as laboratory
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includes researchers from ten departments, and three areas of research have been identified for strategic development: materials research, integration of batteries with power electronics, and safe energy
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genomic data, the lack of advanced analytical frameworks has hindered forensic efforts. This project aims to develop and apply AI-based methods to predict the origin and dispersal patterns of genomic