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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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of communications and marketing, and take initiative in a professional environment that encourages learning and innovation. What You’ll Do: Collaborate directly with your sponsor and their team on communications and
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: Durham, North Carolina 27708, United States of America [map ] Subject Areas: Electrical and Computer Engineering / Engineering Physics , Quantum Engineering , Machine Learning Appl Deadline: 2026/10/01 04
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: Durham, North Carolina 27708, United States of America [map ] Subject Areas: Computer Science / Augmented Reality , Programming Languages Electrical and Computer Engineering / Machine Learning Appl
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of life science research experience. · Experience working with mouse models of disease. · Technical aptitude for learning and executing complex experimental techniques for molecular biology, cell-based
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planning, scheduling, training, equipment selection, student-athlete development and any other duties as assigned by the Head Coach. Emphasis will be placed on learning how to instruct, coach, and prepare
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with causal inference methods or machine learning approaches Demonstrated experience in scientific writing and publication Ideal for candidates who: Have recently completed (or are near completion of) a
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. Postdoctoral Associate - Multi-agentic Coordination, Self-learning and AI Safety in Health Be You. The Department of Surgery at Duke University Medical Center seeks a Postdoctoral Fellow to lead research in
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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited
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, bioinformatics, or a related discipline. The successful candidate will lead computational research projects applying advanced statistical, machine learning, and artificial intelligence approaches to large-scale