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Application Deadline 31 Dec 2027 2027-12-31 8:00:00 2027-12-31 18:00:00 Europe/Paris Postdoc position in Machine Learning for Integrative Genomics The Machine Learning for Integrative Genomics team (https
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(JARVIS) for data-driven materials design" https://www.nature.com/articles/s41524-020-00440-1 2. https://jarvis.nist.gov/ 3. https://www.nist.gov/people/kamal-choudhary Keywords Machine learning
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more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/306376/phd-research-fellow-in-machine-learning-for-cognitive-neuroscience Where to apply Website https://www.jobbnorge.no
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approaches for drug design by combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038
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University of California, San Diego | Estancia de San Diego, Guanajuato | Mexico | about 8 hours ago
Position overview Position title: Moore Postdoctoral Fellow Salary range: A reasonable salary range estimate for this position is $69,073 - $71,632. The posted UC academic salary scales ( https
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requirements of Monash for PhD (https://www.monash.edu/graduate-research/future-students/apply); Knowledge of machine learning (would be a plus if familiar with NLP and Medical AI); Knowledge of cybersecurity
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SEMIAMOR "Machine Learning for Column Generation" See detailed description at https://lipn.fr/~leroux/static/phd_semiamor_cg.pdfLaboratory: Laboratoire d'Informatique de Paris Nord Field of
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International Relations, Connected\Politics Lab, RINN AI UCD. The Research Data/ML Engineer will lead the retrieval, evaluation and machine-learning research that determines the accuracy and trustworthiness
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https