82 parallel-and-distributed-computing-phd Postdoctoral positions at Stanford University
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-author papers and present at conferences with the goal of helping the Fellow continue to build out a robust program of research. Timeline Application review will begin January 30, 2025. Applicants
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., mechanical engineering, materials science, chemical engineering, electrical engineering, environmental engineering, computer science). About the group: Group alumni and their current positions (link is
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Health Epidemiology and Population Health Med: PCOR Health Policy Neuroscience Institute Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Science Postdoc Appointment Term: 1-3 years
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be to optimize CAR T-cell function in the context of pediatric solid tumors. Required Qualifications: This position is for a candidate with a PhD or MD/PhD with wet lab experience, including cell
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Summer 2026, with the potential for renewal. Required Qualifications: PhD in education, economics, sociology, computer science, public policy, or a related field Demonstrated expertise in PK-12 education
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partners in genomics, cancer biology, and clinical research, providing opportunities to work with diverse biological systems and translational applications. Required Qualifications: PhD in bioengineering
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healthcare domains preferred Experience with mixed methods research approaches preferred Doctoral degree (PhD, MD, or equivalent) conferred by start date Required Application Materials: Curriculum Vitae Cover
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Postdoctoral Affairs. The FY25 minimum is $76,383. The Stanford Natural Capital Project seeks candidates to support a research program aimed at the implementation and scaling of natural capital approaches within
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testing of the Identity Project and the E4 Teacher Professional Development program in the United States – identifying feasible and effective strategies to support educators as they prepare to implement
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connections between the lab, classroom, and society. Required Qualifications: Highly motivated postdoctoral researcher with extensive experience with item response theory models, computer adaptive testing, and