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Safety Committee by reviewing proposals for the use of radioactive materials and x-ray-producing machines, conducting specialty audits and providing consultations to researchers related to the use
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific vision
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and machine learning models. To be successful in this role, you will have excellent communication skills and written English, strong quantitative and analytical skills, the ability to work creatively
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for Machine Learning at the Department of Informatics, University of Oslo, Norway. Starting date no later than October 1st, 2026. The appointment is for a fulltime position and for a period of 2 years. Job
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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Triple Negative Breast Cancer Using Machine Learning”. We seek to appoint a creative and motivated individual to use machine learning (ML) to identify why some patients with triple negative breast cancer
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48 Salary Range $62,941-103,834/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https://hr.uky.edu/employment
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Babinski, PhD. This position will report to Research Professor Leslie Babinski. CIDR is a school-based research and professional learning initiative designed to strengthen adolescent wellbeing and literacy
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in