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collaborative ADAPTS precision medicine program. The research of the Cancer Signalling Research Group and their collaborators have uncovered therapeutic vulnerabilities in diffuse midline glioma (DMG), a
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 6 hours ago
Intelligence and the Life Sciences. We are building an AI-native, closed-loop research engine where automation, computation, and intelligent agents work together to decode, model, and rewrite biological circuits
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only of storing information, but also of manipulating, organising, and retrieving it through molecular data structures analogous to those used in computer science. Building on our pioneering experimental
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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Computer science » Informatics Researcher Profile First Stage Researcher (R1) Application Deadline 15 Sep 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per
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About the Hubrecht Institute The Hubrecht Institute is a research institute focused on molecular and developmental biology. Because of the dynamic character of the research, the institute has a variable number of research groups, around 20, that do fundamental, multidisciplinary research on...
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7 Aug 2026 Job Information Organisation/Company Technical University Of Denmark Department DTU Compute Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1
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fully funded 3.5 PhD (GTA) starting in January 2027 for the following disciplines; Biochemistry, Cell Biology, Chemistry, Computational Biology, Genetics, and Sports, Exercise and Rehabilitation Sciences
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, a strong degree in computer science, cybersecurity, mathematics, or a related subject. Experience with cryptography, machine learning, or systems implementation is valuable, as are solid programming
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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited