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to sustainability. Communicating the results in scientific publications and conference presentations Co-supervising PhD and MSc students working on the project Contributing to new research ideas and (co)-applying
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of the most livable countries in the world, with a high quality of life, safety, excellent education system, and competitive economy. Read more about living in Oulu Who are you? You must hold a PhD degree in
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addition to research, you will also be expected to take part in the supervision of PhD students and the teaching activities of the research group. Your network and team Currently, our research group consists of 1
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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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-based products (e.g. oatmeal, tofu, protein concentrate preparations). The research is led by Matti Ruuskanen, PhD, Docent in Microbiology, who works as a University Lecturer in the Food Sciences Unit
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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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subject ranking) and is currently investing heavily in life science research (see https://www.helsinki.fi/en/helsinki-institute-of-life-science) . The research team currently consists of 4 post docs, 4 PhD
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. Essential qualifications PhD in computational statistics, bioinformatics, systems biology, or a related field. Strong expertise in statistical methods, including machine learning approaches, for analysis
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end date may change, in which case the position ends accordingly. Job description This position is integrated into a high-impact Horizon Europe research project. As a PhD candidate, you will conduct
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campus. Who we are looking for Requirements Applicants must have: A PhD in Immunology, Cell Biology, Biochemistry, Biology, Medicine, Biomedical Sciences, or another relevant life science field Significant