892 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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Engineering and will become part of the national graduate school FOFOS – Research School for the Transformation of the Public Sector (https://www.mdu.se/forskning/forskarskolor/forskarskolan-fofos ). FOFOS is
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at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment: Temporary employment 24 months, with the possibility of extension. Scope: 100% Start date: As agreed
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position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years. A starting salary of 34,550 SEK per month (valid from May 25, 2025
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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. The department will provide support with language learning. Eligibility The applicant must meet the following qualification requirements: PhD or equivalent academic qualifications research expertise in
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practices. Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ WIFORCE Research School Do you want to contribute to the future sustainable use
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-2026 URL to this page https://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=10072&rmlang=UK
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aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn