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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This project aims aims at understanding the role
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Application Deadline 21 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2025 Is the job funded through the EU Research Framework Programme? Not
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the area of efficient and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design
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Sectional Interventional Radiology fellowship program provides unique advanced clinically rigorous training in Abdominal Imaging, Image Guided interventions and Clinical Research. Imaging training broadly
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are required, as well as experience with machine learning, and some familiarity with the major bioinformatics tools/databases. Experience with high performance computing and protein function and/or structure
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energy into acoustic waves, which can then be used to generate electricity or manage heat at the microscale. The goal is to improve the performance, efficiency and scalability of these microscale systems
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medical datasets (e.g., electronic health records data or medical images) Ability to use high performance computing cluster For consideration, applicants need to submit a cover letter, curriculum vitae with
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 6 hours ago
to develop and publish innovative computational methods and to contribute to high-impact translational studies of autoimmunity. Our overarching goal is to define the genetic underpinnings of autoimmune skin
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of hollow core optical fibers for high capacity and quantum telecommunications applications. Additionally, the post-doctoral officer will collaborate with project partners to test and evaluate the performance
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cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and