915 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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to apply Website https://www.hb.se/en/about-ub/work-at-ub/how-to-apply-for-a-job-with-us/ Requirements Research FieldTechnology » Materials technologyEducation LevelMaster Degree or equivalent Skills
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods
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of working with motion capture, eye tracking, machine learning, or other advanced behavioral analyses or related research experiences. A consistently excellent academic track record is required, including
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to collaborate effectively with colleagues across all levels, both within and outside the organisation Are a self-starter with a passion for learning new technologies Take initiative to solve problems Are creative
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are widely used in a variety of projects, in particular in the EU funded projects AVENGERS (which is coordinated by Lund University, https://avengers-project.eu) and IM4CA (https://im4ca.eu). Work duties The
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: Learn the analysis programs. Populate the SpecTable library with newly collected data sets. This is a unique opportunity to gain hands-on experience in a cutting-edge research environment and contribute
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. Location: SciLifeLab , Solna https://ki.se/en/research/research-areas-centres-and-networks/research-groups/uncovering-the-molecular-and-physical-principles-governing-early-embryonic-division-and-nuclear
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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well as in urban areas. See also: https://www.slu.se/en/about-slu/organisation/departments/ecology/ About the position The researcher will work in the field (in southern Sweden), with statistical analyses, and
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link