71 software-verification-computer-science Postdoctoral positions at Duke University in United-States
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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 research
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The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment The Postdoctoral Appointee functions under
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. Minimum Requirements: PhD or equivalent doctorate (e.g., ScD, MD, DVM) in psychology, psychiatry, neuroscience, biostatistics, bioinformatics, computer science, or a related field. Research background in
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. This computational immunobiology postdoctoral position is appropriate for a candidate who is enthusiastic and willing to undertake multiple molecular biology and computational approaches to evaluate host immunity
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clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee functions under the supervision of a mentor
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, United States of America [map ] Subject Areas: Computer Science Machine Learning Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Appl Deadline: none (posted 2025/08
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, neuroscience, physiology, physics, or computer science · Be a proficient programmer and experience in Python, MATLAB, NEURON, COMSOL, and / or git are assets · Be familiar with neural biophysics and
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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 research
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research or scholarship. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research training under
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control