900 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab"-"IFM" positions at Nature Careers
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materials synthesis, advanced operando characterization, and lab scale testing. We use robotic, high-throughput methods, and data science to accelerate novel sustainable materials discovery. PhD Position
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, interests, and career goals align with its objective PhD diploma or a letter/information indicating the expected defense date Transcript of all modules and results from university-level courses taken List
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use cutting edge machine learning and data mining techniques to gain novel insights and advance our understanding of the rules defining T and B cell immunogenicity. If you are looking for the best
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Faculty Position, Department of Pharmacy and Pharmaceutical Sciences - Pharmacoeconomics / Health Ec
, translational, and clinical investigators conducting high-impact, interdisciplinary research. Investigators have access to resources developed at St. Jude relevant to pediatric cancer, including genomic data in
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to data preparation and ultimately quantification. You will oversee the research PACS at the NCT and be the main contact person for questions about imaging processing, analysis, and archiving. Your Profile
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and fire tests Data evaluation, interpretation, and scientific discussion of results Documentation, reporting, and presentation of results at scientific conferences and publication of results in
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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to requests, confirms understanding of routine needs, and provides accurate answers. Shares information within team as directed. Manages own time well to plan work and meet daily task needs. Executes routine
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, it will be important for candidates to have familiarity with basic coding practices to coordinate data collection across multiple platforms (e.g, coordinating calcium imaging or optogenetic delivery
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves