73 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "Dr" "P" Fellowship research jobs at Nature Careers
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Postdoctoral Fellows to join a dynamic, fully funded research program investigating how environmental exposures and inflammation drive hematopoietic stem cell dysfunction, clonal hematopoiesis, and the
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The Intramural Research Program (IRP), National Institute on Drug Abuse (NIDA), a research component of the National Institutes of Health (NIH), Department of Health and Human Services (DHHS) has
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departments and take up a key role in achieving the highest standard of quality in all aspects of its teaching, research and clinical programmes; fostering academic collaboration within and outside the Faculty
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. Located in
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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, in vitro models, and large collections of well-annotated clinical specimens. We employ state-of-the-art computational biology/bioinformatics approaches to dissect acute and adaptive responses to RAS
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foundation in related fields who are eager to learn and contribute to our research program. Technical duties include but are not limited to: Lead independent research projects, including hypothesis development
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of Dr. Andrew Lane (https://lanelab.dana-farber.org/), within the Hematologic Neoplasia Division of the Department of Medical Oncology at Dana-Farber Cancer Institute. Located in Boston and the
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Center Information The successful candidates will join the research groups led by Dr. Yang Xie and Dr. Guanghua Xiao within the Quantitative Biomedical Research Center (QBRC). QBRC fosters a highly
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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts