87 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD scholarships at Nature Careers
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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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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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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
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, (bio)informatics, and multimodal data analysis. The research group focusses on the mechanisms of Hypothalamic-Pituitary-Gonadal (HGP) axis regulation that governs human reproduction. The group
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. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract Type: Fixed Term Contract
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, (bio)informatics, and multimodal data analysis. The research group led by Dr. Johanna Raidt focuses on the identification of known and novel MMAF- and PCD gene variants using large patient cohorts
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combine interdisciplinary research in molecular, structural, and cell biology as well as in physiology, biophysics, epi /genetics, (bio)informatics, and multimodal data analysis. The Eble group investigates
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-weighted magnetic resonance imaging to comprehensively characterize the tumor microenvironment (TME). Tasks will involve the development of improved biophysical models and corresponding MRI data acquisition
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in vitro work, including work with primary cells isolated from human bone and bone marrow, and characterize these primary cells using various cell biology and molecular biology methods Establish data
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state-of-the-art approaches, including next-generation sequencing, functional genetic screens, and transgenic model systems. Further information is available on our homepage and via our publications in