72 assistant-professor-computer-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Stanford University
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The Precision Neurotherapeutics Lab (precisionneuro.stanford.edu ) in the Department of Psychiatry and Behavioral Sciences at Stanford University is seeking a full-time Assistant Clinical Research
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hour. Duties include: * Schedule, monitor, and supervise Animal Care Assistants performing animal husbandry and sanitation duties to ensure program and facility compliance for multiple locations
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. Optional: mentor junior trainees and contribute to grant writing activities. Training and Environment The postdoctoral fellow will work under the mentorship of Dr. Titilola Falasinnu, Assistant Professor in
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development, and coordination of internal support activities. They will work with OOD colleagues, donors, volunteer leaders, faculty and other university staff to assist in establishing and maintaining
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, and the individual will also be responsible for overseeing the lab’s flow cytometer and assisting in laboratory management with others on the team. The individual will also be expected to onboard, teach
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(Administrative Associate 3) to provide administrative or operational support with limited supervision to 4-6 faculty and their program managers. Faculty will have varying levels of support needs ranging from
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. · Contribute to publication of findings as needed. Participate in the preparation of written documents, including procedures, presentations, and proposals. · Help with general lab maintenance as needed
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documents for IRB submission in compliance with all local, state and federal regulations; advise the IRB of amendment changes to the protocol and complete annual protocol renewals. Recruit, screen, assist in
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interest in translational science. The postdoctoral fellow will work closely with Dr. Vivek Charu and Dr. Brooke Howitt. Required Qualifications: PhD in Biostatistics, Bioinformatics, Computational Biology
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the scope and impact of our studies. Current research themes include: The impact of GLP-1 receptor agonists on metabolic outcomes and surgical decision-making in bariatric patients Computer vision analysis