341 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" research jobs at Nature Careers
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vitae, a brief cover letter outlining their research experience and interests, and contact information for three references via email to: sgong@engr.wisc.edu Research Group Website: https
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decisions are anticipated to be made by April 1st, 2026. Applicants must apply online at: https://www.princeton.edu/acad-positions/position/40521 Applications must be completed by January 31, 2026 at 5:00 PM
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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collaborators. With the help of statistics, machine learning and pathway- and network- and analyses, the goal is to improve the mechanistic understanding of disease- and treatment-associated alterations in
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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. Antonio Scialdone’s group at Helmholtz Munich, a leading European hub for AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models
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informatics, molecular simulation, computer-aided molecular design, and chemically aware machine learning. Our mission is to enable a deeper interrogation of biology through the integration of chemistry
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Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in