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supportive environment to join our team. A PhD degree is required with training in neuroscience, human physiology, psychology, pharmacology, and/or a related field. Experience with imaging (MRI / fMRI or other
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Radiation Oncology, and Electrical and Computer Engineering. Job Description: The Computational Image analysis team led by Dr Barisoni and Lafata aims to advance existing imaging techniques and develop novel
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surrounding targeted therapeutic development. Current project teams employ synaptic physiology, in vivo chemicogenetic circuit manipulations, behavioral phenotyping, 2PLSM calcium imaging of direct and indirect
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Responsibilities: • Conduct advanced research on the binding properties of noble gases to neuronal receptors. • Investigate the specific roles of noble gases in anesthesia and brain protection. • Collaborate across
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advanced whole organ imaging, scRNAseq, and spatial transcriptomics for reconstructing tumor initiation programs at the single cell level. Recent high-impact work has utilized our novel Cancer rainbow
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advanced whole organ imaging, scRNAseq, and spatial transcriptomics for reconstructing tumor initiation programs at the single cell level. Recent high-impact work has utilized our novel Cancer rainbow
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. The Postdoctoral Appointee holds a PhD. (or PhD. candidate) or Knowledge, Skills, and Abilities. University. research requirements or other equivalent doctorate Ph.D. in life science (e.g.biochemistry, biophysics
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Conduct independent research activities under the guidance of a facultymentor in preparation for a full time academic or research career. A postdoctoral Research Associate (computational biology and
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but are not limited to graft-versus-host disease as well as hematopoietic and T cell reconstitution following transplantation and radiation exposure. Qualifications: A doctoral degree such as MD or PhD
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for healthcare data analysis, with the opportunity to develop corresponding statistical theory if interested. Conduct research in areas of interest including, but not limited to generative models for biomedical