71 distributed-computing-associate-professor Postdoctoral positions at Stanford University
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, with additional mentorship from Professor Bobby Bartlett. The program is structured to support the development of a strong research pipeline, including the opportunity to coauthor work with Professors
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the Cancer Data Science Core at the Stanford Cancer Institute (link is external) , directed by Dr. Summer Han, Associate Professor at Biomedical Informatics Research and co-directed by Dr. Allison Kurian
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analyses of electronic health record (EHR) data. The postdoc will work with Assistant Professor Zachary Butzin-Dozier (Department of Pediatrics, Division of Clinical Informatics, and Department of Medicine
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a highly motivated postdoctoral scholar in hematology, stem cell biology, and cancer biology to work in the laboratory of Professor Asiri Ediriwickrema in the Division of Hematology at Stanford
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research initiative at the Stanford Center on Early Childhood. Professor Jelena Obradović and her team at the SPARK (Stanford Project on Adaptation and Resilience in Kids) Lab have designed a battery of
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(but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $77,000-$80,000 The laboratories of Dr. Marlene Rabinovitch, Professor
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are seeking a postdoctoral scholar in computational biology to work in the laboratory of Professor Sylvia Plevritis in the Department of Biomedical Data Science at Stanford University. This research opportunity
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backgrounds trained in chemistry, chemical biology, microbiology, and/or biophysics fields. We have launched a collaborative antibacterial drug design program integrating chemical biology and mechanistic
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to a high-impact global program with a mission to create a healthier world by addressing lead contamination at the source. Project Unleaded conducts policy-relevant research that positively impacts
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multidisciplinary team studying the genomics of neurodegenerative diseases, with a special focus on Alzheimer’s Disease (AD). Current research focuses on using novel methods to detect genetic associations with