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including researchers in archaeology, anthropology, genetics, evolution, biodiversity and more, as well as to e.g. museum staff and contract archaeologists. The interest for the unit’s services is large and
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SciLifeLab, aims to recruit and train the next-generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total
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, lineage-tracing, and computational approaches to address clinically relevant questions in cancer and drug development. Our work is carried out in close collaboration with national and international partners
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creating inclusive environments. Flexible and Supportive: Tailored training and career development designed to balance professional growth with personal commitments. State-ot-the-art Research: Engage in
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division The Division of Biomedical Engineering is part of the Department of Materials Science, and Engineering at the Ångström Laboratory. We perform research within the development of miniaturized
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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Biodiversity Subject description The subject concerns biodiversity in a wide sense; variation and evolution within species, between species and among communities across space and time. It includes the study of
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of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as flow matching. Therefore, the doctoral
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different research projects in the lab, and will also have the possibility to develop their own project. Successful candidates will have the opportunity to work in a vibrant and highly collaborative
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep