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perception, and validate experimental results using real-world data obtained with citizen science. The project will also model the effects of nature on time perception at the landscape scale under different
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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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new characterization techniques. The research needs to be connected and communicated within the project and length-scale bridging modelling tasks are included. Part of the project collaboration happens
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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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and experimental models. Our research focuses on combining large-scale molecular data - including metabolomics, lipidomics, genomics, proteomics, glycomics, and microbiome data - with advanced
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during cancer, inflammatory diseases, and vaccination. The successful candidate performs laboratory experiments, including in vivo models, analyzes tissue and cell samples using imaging and omics
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The University of Helsinki (https://www.helsinki.fi/en ), founded in 1640, is one of the world’s leading universities for multidisciplinary research. The university has an international academic
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seeking to recruit a motivated Postdoctoral Researcher to work in the theory projects within the Centre of Excellence in Quantum Materials (https://www.qmat.fi ). The research will be guided by Professor
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‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods will be designed for near‑term (NISQ‑era) deployment, with models evaluated for expressivity, training stability
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of Helsinki, Finland working in the research groups of Prof. Craig Primmer and Dr. Tutku Aykanat (http://www.helsinki.fi/evolution-conservation-and-genomics ) as a part of several related research consortia