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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
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staff with excellent interdisciplinary knowledge and specialized, state-of-the-art expertise in software engineering, computer visualization, and data science. As a faculty member, the applicant is
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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systems, and/or human brain. Use of artificial intelligence and machine learning approaches is a plus. Details of current faculty and research in the Department of Anatomy & Neurobiology can be found
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and
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Immunology, and to teach and mentor graduate students. Salary and academic rank are commensurate with experience; excellent benefits and highly competitive startup packages are offered. The CVHII is part of
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Priorities: We seek applications across all AI domains, with emphasis on: Foundational AI : Machine Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers