533 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" PhD research jobs
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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-good university degree in economics - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) - a high motivation and the
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, statistics, machine learning) - a high motivation and the ability to work independently with a strong team orientation - excellent spoken and written English and the will to acquire a certain working language
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in English. Mark your application with the reference number below. Closing date for application: 13 April 2026 Reference number: 2464-2026 URL to this page https://web103.reachmee.com/ext/I003/583/main
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, individualized education. Faculty are committed to creating a student-centered learning community that embraces multiple viewpoints. It is a department in which learning, research, and professional activity inform
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of roles and tasks. Strict expertise in all the technologies is not required. However, a great attitude and willingness to learn is a must. Flexible Work location The selected candidate will offer
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Cosmology/Particle Astrophysics AI/Machine Learning Theoretical Physics / Theoretical High Energy Physics , Theoretical particle physics High Energy Physics / BSM , Dark Matter , Electroweak Symmetry
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Computer Engineering, please visit https://ece.au.dk/ See more about our activities on LinkedIn: https://www.linkedin.com/company/au-ece What we offer The department offers: a well-developed research
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funds from UMass Chan. More information can be found on the lab website https://zhou-group.org/ Applicants should hold a Ph.D. in immunology, microbiology, or a related biomedical science. The ideal
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eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary We have immediate availability for postdoctoral associate researchers in experimental particle physics on the CMS