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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 hours ago
) | Computer Vision The Optics & Sensing Laboratory (OSLab) at the Max Planck Institute for Intelligent Systems in Tübingen (Germany) has an open position for a Doctoral Researcher for the project “WeGaze
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the wind/renewable energy training and research elements of the CDT programme. Funded by Statkraft and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of data
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extension to other immunotherapy-treated cancers to enable cross-cancer comparison and broader generalisability. The project will leverage two complementary data sources: the TrinetX global research network
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PhD Scholarship - Novel methods to enhance the use of routinely collected linked data for the evaluation of government policies related to healthy ageing Job No.: 691415 Location: Frankston
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At the Leibniz Institute of Atmospheric Physics (IAP), a part-time position (75%) in the “Satellite Data Analysis” working group is available as PhD Student (f/m/d) The position is initially offered
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The Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and Queensland Academy of Sport (QAS) are leading a consortium of government and industry organisations in sports, sports and
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic bioinformatics techniques to respiratory samples and developing analysis and interpretation approaches
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complete transcripts For more information please contact Prof. dr. Filip Van den Bossche, mail: filip.vandenbossche@kuleuven.be Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60633428
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This exciting fully funded PhD, will address the challenge of forever chemicals in drinking water. The aim of this research is to develop a smart data predictive model that will support utilities