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Field
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5) to support clinical research protocols. Join a high-impact, interdisciplinary program at the intersection of epilepsy, neuromodulation, and sleep biology. We seek a motivated, ambitious research
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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degrees in educational leadership, marine biology, nursing practice and psychology; and many distance learning options, including clinical research, an accelerated RN-to-BSN program, an Executive M.B.A
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 11 hours ago
degrees in educational leadership, marine biology, nursing practice and psychology; and many distance learning options, including clinical research, an accelerated RN-to-BSN program, an Executive M.B.A
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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fostering translation and innovation. Its vision is to transform health and healthcare for all, achieved through innovative research and education at the convergence of engineering, medicine and biology
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one day a week on campus. Job description The computational biologist will be expected to: Lead the development of acoustic detection and classification algorithms for marine mammals. Evaluate algorithm
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software. The research fields range from molecular biology to astrophysics. Your research agenda should overlap with one or more research areas at HITS: Complex simulations across scales: from molecules
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts