18 computer-aided-design Postdoctoral positions at UNIVERSITY OF HELSINKI in Ireland-University-Ranking-2024
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-science ) carries out research on chemistry and its applications at an international level and provides academic teaching based on high quality research. The Department of Computer Science is a leading unit
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programme. Develop and optimise retinal organoid and stem cell-based disease models. Design and evaluate gene therapy and gene editing constructs. Contribute to mentoring students and junior researchers
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interviews with the applicants. The topic of the research plan must suit the profile of the doctoral programme. Successful applicants will become university-funded doctoral researchers at the University
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design, and/or environmental justice approaches and responses to the climate crisis. The position is linked to the Finnish Research Council Profi9 support for a project on Climate Democracy, led by
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11 Jul 2026 Job Information Organisation/Company UNIVERSITY OF HELSINKI Research Field Biological sciences Computer science Researcher Profile Leading Researcher (R4) Application Deadline 16 Aug
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treatment resistance in ovarian cancer. Vähärautio lab (https://vaharautiolab.org/) at the Medical Faculty, University of Helsinki, is seeking a bioinformatician or a computer scientist with strong
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. Employment starts as soon as possible. Position description The postdoctoral position funded by the Research Council of Finland aims to design closed-loop dissolution/activation laboratory and scaled-up
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assessing applicants’ qualifications, attention will be paid to international academic activities, including high-quality peer-reviewed publications. A University Researcher typically has at least ca. five
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assessing applicants’ qualifications, attention will be paid to international academic activities, including high-quality peer-reviewed publications. Applicants should be prepared to provide proof
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on health data as well as training AI models on health data across national borders. Key responsibilities Design, implement and benchmark machine learning models for large-scale health datasets consisting