54 senior-lecturer-distributed-computing Postdoctoral positions at Stanford University
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team with other lab members. Our lab is an inclusive space that fosters learning & curiosity, promotes team work and values mentorship to drive an innovative research program that pushes the boundaries
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on manuscripts, presentations, and research proposals Required Qualifications: PhD in psychology, neuroscience, biostatistics, computer science, or a related field. Strong interpersonal and technical skills
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generation technologies Preparing quarterly and final reports for research grants Writing research proposals, peer-reviewed publications, and other program activities. Advising and mentoring students
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experience using mouse models of disease. Priority will be given to applicants with prior training in pulmonary biology, or candidates with expertise in computational biology or single cell transcriptomics
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, Applied Mathematics, Statistics or related computational field. Superb quantitative background, strong coding skills (e.g., Python, R). Expertise in infectious disease modeling. Strong record of peer
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or the interest in learning programming is highly desirable. A successful candidate will interact closely with computational biologists and be responsible for designing and executing experiments that will, in part
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Posted on Wed, 08/13/2025 - 18:56 Important Info Stanford Departments and Centers: Biomedical Informatics Neurosurgery Epidemiology and Population Health Biomedical Data Sciences Postdoc Appointment
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work on a priority research program in which individuals are assessed with functional MRI, behavioral, and symptom measures before, during, and after treatment. Treatment includes selectively targeted
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Posted on Thu, 03/06/2025 - 16:51 Important Info Deprecated / Faculty Sponsor (Last, First Name): Fisher, Philip Other Mentor(s) if Applicable: Sihong Liu, Research Associate Stanford Departments and Centers: Graduate School of Education Postdoc Appointment Term: Summer/Fall 2025 through...
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, molecular biology, and in vivo models. Analyze and interpret data, integrating experimental and computational findings. Utilize bioinformatics tools and techniques to analyze high-throughput sequencing data