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closely together with researchers in (data-driven) sciences, industry and society to accelerate data-intensive scientific discovery. eSSENCE is a strategic collaborative research programme in e-science
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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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at the Division of Biomedical Engineering Department of Materials Science and Engineering, Uppsala University Full-time temporary position for two years starting in September 2026, or as agreed upon
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KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health Job description Tissue organization is achieved by the genome encoding both cell type