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develop research. Extraction of Patient Reported Outcome Measures. • Collaboration with the PhDs at the laboratory, division, department, and University. Development of data-sharing agreements and
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advancing research in neuroscience, human physiology, psychology, and pharmacology. Your work will contribute to meaningful discoveries and help shape the future of clinical research. Be Bold. This is your
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. Education/Experience: Ph.D. or equivalent doctorate (e.g., Sc.D.., D.V.M.) in Pharmacology, Neuroscience, Physiology, Toxicology, Veterinary Sciences or related fields. Minimum Qualifications Other Credential
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. The incoming postdoctoral fellow will work closely with this technician to carry out experiments and help drive the research program forward. Requirements: The ideal candidate will hold a Ph.D., M.D., or
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translational neuroscience is preferred. Expertise in neurobiology, electrophysiology, mechanotransduction, ultrasound, or in vivo mouse work is highly desirable but not required. Lab Background: We are a high
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) in medical physics, biomedical engineering, electrical engineering, or computer science. Candidates with non-US degrees may be required to provide proof
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of experiments, including raw experimental data and laboratory notebooks. Monitor progress of research projects and coordinate with Principal Investigator and Program team to stay on budget and schedule to meet
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projects and coordinate with Principal Investigator and Program team to stay on budget and schedule to meet the milestones and deliverables. Follow standards of responsible conduct in research. Comply with
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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
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computational models of the immune response for multi-scale epidemic models. This position offers an excellent opportunity for recent graduates interested in applying quantitative and computational methods