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for interdisciplinary applied AI research, education, and workforce development. Established with support from the UT System Regents' Research Excellence Program (RREP), AAII represents a landmark investment in UTEP's
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View Vacancy -- Scientific Computing Officer - Scientific Computing- Structural Studies - LMB 2801 Open Date 20/03/2026, 08:00 Close Date 19/04/2026, 23:55 Research Institute MRC Laboratory
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Faculty Position — Research Scientist in Cardiology, Cardiac Regeneration and Translational Cardiova
an exceptional research scientist to establish a cutting-edge program addressing fundamental challenges in cardiovascular disease through innovative approaches in regenerative medicine, cardio-oncology, or related
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the EU Research Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description NOTICE OF OPENING OF AN INTERNATIONAL SELECTION PROCEDURE
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requires expertise in Computer Science, Statistics, or a similar field. Experience with machine learning, genetics, and/or bio-informatics is strongly preferred. The postdoc will work together and within a
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the results and improving the algorithms. It will also involve extensive literature reviews. Applicants must have an undergraduate degree in computer science, have significant experience with deep learning with
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Fermilab, Computational Science and Artificial Intelligence Directorate Position ID: FNAL-CSAID-RESEARCHASSISTANT [#30908, FermiEAC-RA] Position Title: Position Type: Postdoctoral Position Location
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design, data analysis, and documentation of experiment results. Job Description Primary Duties & Responsibilities: Develops algorithms and computer software for omics-based data sets [high-throughput
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; addressing the spread of misinformation and disinformation in social networks; using algorithms or computer simulations to study gerrymandering; or the role of information visualization to investigate and
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variety of Georgia Tech initiatives, including the Algorithms and Randomness Center (ARC), the Center for Machine Learning (ML@GT), the Center for Research into Novel Computing Hierarchies (CRNCH), and the