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, United States of America [map ] Subject Areas: Machine Learning Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Appl Deadline: none (posted 2025/08
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, United States of America [map ] Appl Deadline: (posted 2025/09/04, listed until 2026/02/20) Position Description: Apply Position Description Postdoctoral Associate – Scientific Machine Learning for Multiscale Biological
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., M.D., D.V.M.) Preferred Qualifications:. Detail-oriented, very well organized, and approach laboratory procedures with critical thinking. Strong initiative and eagerness to learn. Outstanding problem
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, genomics, computer science, bioinformatics, or a related discipline. The successful candidate will lead computational research projects applying advanced statistical, machine learning, and artificial
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research conferences, and through publications. · Assist in writing grants. · Coordinate lab experiments/timelines. · Supervise, train and instruct new personnel in laboratory techniques and procedures
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Overview We are seeking a highly motivated postdoctoral researcher with expertise in artificial intelligence and machine learning (AI/ML) to join our interdisciplinary team at Duke University. The postdoc
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Center is seeking a Postdoctoral Researcher to work on ion trap quantum computer and quantum network projects, supporting/advancing research in quantum information science. The position involves designing
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learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in the administration of both its employment and educational policies. Duke
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pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends
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conditions), sexual orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of