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documentation What we offer A friendly, international research environment with high-quality infrastructure Training opportunities and professional development Comprehensive employee benefits (occupational health
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Environmental Sciences comprises roughly 40 research groups which employ 40 principal investigators and 120 researchers. The research programme is situated in the Viikki science park. https://www.helsinki.fi/en
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, at the latest. Want to know more? For more information about the position, please contact Head of Administration Veli-Pekka Heiskanen (veli-pekka.heiskanen@helsinki.fi ) tel. 02941 57580 and Development Manager
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. The initial salary is €4064, and the contract includes occupational health care. Our vast array of professional development opportunities means you will grow and learn, having the chance to participate actively
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, gating strategy development, and cell sorting Sample preparation and dissociation protocols for nuclei and/or cells, ideally across multiple tissues including challenging tissues (e.g., skin) High
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methods and software development. The objective of the Unit is to balance basic and industrially applicable research, having both performed with excellence in each of the research areas. The positions will
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programs The University of Helsinki provides its staff with occupational health and sports services as well as professional development opportunities (https://www.helsinki.fi/en/about-us/careers/why
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. Applications are invited for a full-time Postdoctoral Researcher in development of plasmonic nanopore for single molecule sequencing by surface enhanced Raman spectroscopy (SERS) position under supervision by
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artificial intelligence/geospatial AI, methods of machine learning and deep learning development of computer vision applications and image recognition methods analysis and production of big data, including
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning