86 computational-physics "https:" "https:" "https:" "https:" "UCL" Postdoctoral positions at Duke University
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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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. The appointment is viewed as preparatory for a full time academic or research career. The appointment is not part of a clinical research training program, unless research training under the supervision of a senior
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lab members, and collaborate with colleagues across the Duke research community. Required Qualifications at this Level Education/Training: PhD in Physics, Electrical/Computer Engineering/Quantum
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or scholarship, and may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless
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activities ● Present results at collaboration meetings and scientific conferences Required Qualifications: ● Ph.D. in Physics, Astronomy, Astrophysics, Computer Science or a related field by the start date
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or scholarship and may include teaching responsibilities The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program, unless
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students, support new group members, and collaborate with colleagues across the Duke research community. Required Qualifications: Education/Training- PhD, physics, mathematics, quantum information/mechanics
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is generally preparatory for a full time academicor research career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the
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is generally preparatory for a full time academicor research career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the
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addition to pursuing their own research agenda, we seek applicants with experience in survey design and computational methods, and working with complex large-scale data. Successful candidates will have completed a Ph.D