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Field
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Machine Learning Scientist to join the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including
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The Genetics Department at Stanford University is seeking a Software Developer 2 to conceptualize, develop, supervise, and implement novel computational approaches for genomics. The successful applicant must
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
. Duties/Responsibilities Analysis (50%) Develop machine learning algorithms to analyze ground magnetic field perturbations Analyze the results using machine learning interpretability techniques
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within the assigned region. Assists in the development and implementation of UCHC’s policies and procedures. Participates in UCHC’s continuous quality improvement program. Corrective action plans
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of 22q11.2 and 3q29 deletion syndromes, two rare conditions that confer the highest genetic risks of schizophrenia. Key Responsibilities: Develop and implement advanced algorithms for analyzing calcium
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Detailed Position Information The Department of Electrical and Computer
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researchers from oncology, radiobiology, computer science, genetics, statistics, and basic/translational clinical research. Our research couples state-of-the-art computational and experimental techniques
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to genetic, genomic, proteomic and/or metabolomic data from hospitalized children; developing predictive algorithms for in-hospital events; investigating pattens and quality of care for hospitalized children
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Health Access Services This position will be responsible for performing essential tasks required for the creation and revision of Epic scheduling decision trees (algorithms) and for leading other Maestro