49 digital-image-processing-phd-scholarship Postdoctoral positions at Rutgers University in postdoctoral
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background. Consideration to interview will also be given to applicants who are in the process of completing the required PhD, MD, or PhD/MD degree. Documentation of the required PhD, MD, or PhD/MD degree
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are invited for motivated scholars with a strong background in synaptic physiology and live imaging to join the laboratory of Pingyue Pan at the Department of Neuroscience and Cell Biology at Rutgers University
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. Consideration to interview will also be given to applicants who are in the process of completing their doctoral degree (PhD, ScD, D.Phil.) in public health/epidemiology or related field of study. Documentation
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candidate(s) must hold a PhD or MD degree in Neuroscience or relevant biological sciences. Candidates in ABD (all but degree) status will also be considered. Prior experience with cell culture, biochemistry
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Qualifications Minimum Education and Experience PhD degree in Neuroscience or related field with a strong publication record, and a minimum of one (1) year experience in at least two of the following 1) animal
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. Performs advanced signal processing and time–frequency analyses of neural recordings. Develops and implements computational pipelines using MATLAB, Python, or similar platforms. Leads manuscript preparation
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. Innovative academic offerings include bachelor’s, master’s, post-master’s, DNP and PhD programs that are preparing nurse leaders of today and tomorrow at campus locations in Newark, New Brunswick, and
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electrophysiology in brain slices and cell cultures. Performs behavioral tests in mice. Performs in vivo 2p imaging in head-fixed mice. Compiles and analyzes data with appropriate conclusions and recommendations in
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are the following: Obtain and maintain regulatory approval. Set up screening algorithms to identify eligible participants. Recruit participants, collect/ process samples. Design data collection tools (e.g., redcap
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at elevated risk for Alzheimer’s disease, as well as other cohorts affected by neurodegenerative conditions. Her research integrates traditional neuropsychological assessments, digital phenotyping, and