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Field
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clinically validate innovative predictive models utilizing AI and machine learning; test cadaveric anatomy study implementation Complete Data collection and finalize evaluation of AI predictive models
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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Medicine, and member of the City of Hope Comprehensive Cancer. The Perry laboratory uses structural biology approaches, together with small molecule and fragment-based drug discovery, computer-aided drug
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of military Service members with extremity amputations. Why should I apply? Under the guidance of mentor(s), you will gain hands-on experience to complement your education and support your academic and
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages
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with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and decentralized control
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/ Teaching and Learning FTE 1.0 FLSA Exempt Scope of Job Trainee position to pursue research as a vital component of their educational mission and professional career development. Works under minimal
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on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML
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foundation models and agentic systems and demonstrated capability to produce workable solutions from theoretical formulations Substantial publication history in top computer vision/machine learning venues
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works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models. Current areas of interest include