216 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" Fellowship positions in United States
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications
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behaving mice, and advanced modeling + machine learning analyses. Please read more about our research at www.apostolideslab.org . Key questions we want to answer are: How do neural circuits extract
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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of computer graphics, human-computer interaction, computer vision, and machine learning. Conducting comprehensive literature reviews in related areas, including deep generative models, image and video synthesis
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University of Tennessee Medical Center at Knoxville | Knoxville, Tennessee | United States | about 21 hours ago
extensive program is not computer-based learning and is led by the Clinical Educator for Perioperative Services. Position Qualification: BSN or ASN Current Registered Nurse licensure in Tennessee or new
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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic