12 phd-software-testing-scholarship Postdoctoral research jobs at UNIVERSITY OF HELSINKI
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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers
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. The appointee is expected to reside in the Helsinki Metropolitan Area during the employment. QUALIFICATIONS AND EVALUATION Applicants are required to hold a PhD in a relevant field, such as memory studies
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funding. The start date is 1 September 2026. The appointee is expected to reside in the Helsinki Metropolitan Area during the employment. QUALIFICATIONS AND EVALUATION Applicants are required to hold a PhD
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activities (approximately 16% of working time) and supervising PhD students in applied economics research at the University of Helsinki. In addition, the researcher can use up to 50 per cent of their working
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applied industrial economics with ample opportunities for individual and collaborative research, acquisition of external research funds, and supervising MSc and PhD students. We seek candidates who have
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funds, and supervising MSc and PhD students. We seek candidates who have completed a PhD in economics or agricultural economics, who have solid training in econometrics and applied microeconomics and
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The position requires: A doctoral degree relevant to the project (e.g., biology, genomics, evolutionary biology) Less than seven years since obtaining the PhD Ability to conduct independent scholarly work Strong
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for your next career stage. Your profile Recent PhD in Cell Biology, Neuroscience, Biochemistry or a related discipline. A strong academic track record, and at least one recent first-author publication
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facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). YOUR PROFILE PhD in biology, mathematics, or a related field Strong background in mathematical
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the candidate's background and interests, ensuring a collaborative and engaging research experience. We seek candidates who have completed a PhD in ecological statistics or environmental economics or a related