17 cognitive-radio Postdoctoral research jobs at Stony Brook University in United States
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in hand by September 1, 2025. Deep knowledge of functional materials and
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in hand by September 1, 2025. Deep knowledge of functional materials and
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. Preferred Qualifications: Extensive experience in constructing succinct zero-knowledge proof systems, folding schemes, and related topics — both at a theoretical level involving security proofs and other
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, such as Psychology, Cognitive Science, Neuroscience, Biomedical Engineering, Computer Science, Psychiatry, Radiology, and Neurology, or General Medicine. Preferred Qualifications: Prior research experience
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, such as Psychology, Cognitive Science, Neuroscience, Biomedical Engineering, Computer Science, Psychiatry, Radiology, and Neurology, or General Medicine. Preferred Qualifications: Prior research experience
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the glutamatergic system or inflammation in depression, as well as the cholinergic system in cognitive decline. These rich datasets will be used for the successful candidate's publications and grant proposals, with
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the glutamatergic system or inflammation in depression, as well as the cholinergic system in cognitive decline. These rich datasets will be used for the successful candidate’s publications and grant proposals, with
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surgical procedures, mouse behavior, extensive knowledge of the basal ganglia and striatum and amygdala. Experience with anterograde and retrograde circuit tracing. Experience with mouse models of compulsive
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or foreign equivalent degree in hand by May 31, 2025. Preferred Qualifications: Knowledge of high energy QCD through experiments at Jefferson Lab, RHIC or LHC and work on EIC/ePIC detector activities. Brief
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peer-reviewed journals and conferences. Preferred Qualifications: Experience with black-box modeling of wind turbines and converter-based power systems. Knowledge of Lyapunov-based methods, nonlinear