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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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. The project combines quantitative modelling of markets and the wider energy system with empirical analysis of how flexibility is created, priced, and traded by market participants. A central objective is to
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genetics, gene therapy, CRISPR-based gene editing, stem cell technologies, and translational disease modelling. We are particularly interested in developing treatments for retinal disorders prevalent in
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the dynamics of therapy-resistance by combining advanced molecular biology method development to multi-omic single-cell analyses of both ex vivo models and clinical tumor specimens. Our novel, in-house
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combining large-scale ecological datasets, species trait data, ecological network analyses, and quantitative modelling. The postdoctoral researcher will also coordinate and lead field resurveys of historical
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goals. Our other research directions of interest include privacy of AI models trained on health data as well as training AI models on health data across national borders. Key responsibilities Design
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collaborators across the Nordics, Baltics and Europe present a fantastic opportunity to pursue your own ambitious research goals. Our other research directions of interest include privacy of AI models trained
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pretraining of clinical foundation models and clinical alignment techniques. Co-supervise PhD and Master's students in the group, and assist in teaching activities. Lead project deliverables and actively
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Foundation Health Model. As a PhD candidate, you will conduct deep-dive research into training pipelines and reasoning techniques for clinical foundation models. You will join an elite, interdisciplinary team
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other researchers (MSc and PhD students, post-docs and project researchers), as well as with an extended network of international collaborators. Job description The selected candidate will work on the ERC