120 programming-"the"-"DAAD"-"UCL"-"U"-"SciLifeLab"-"IMPRS-ML" Fellowship positions at Harvard University
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experience in modeling of atmospheric composition. Additional Qualifications Experience with the GEOS-Chem model and with inverse analyses, strong scientific programming skills. Experience with inverse
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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Environment Forum programming. Fellows will receive stipends of $70,000, medical insurance, additional research support of $2,500, and (for those not already in residence in Greater Boston) $1,500 in moving
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at Harvard University. Basic Qualifications A Ph.D. degree in Bioinformatics, Computational Biology, or related areas Hands-on experience with or a strong interest in bioinformatics programming, including
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programming and communication skills. Experience in analysis of high-throughput sequencing data is highly desirable. Additional Qualifications Special Instructions Required documents: Curriculum Vitae Statement
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, we plan to demonstrate a fully autonomous buggy that uses our EPiC system. This project is a collaboration among Lightmatter, Boston University, and Harvard University. The Lightmatter team is led by
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our Advanced Research Concepts initiative . During the topic ideation process, Fellows work with program managers and other DARPA experts who serve as internal sounding boards. They engage closely with
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Skip to content HARVARD.EDU About Mission / Vision People Annual Reports Contact Us Programs AWS Impact Computing Bias² Causal Inference CrisisReady Fellowships & Funds SPUDS Trust in Science See
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are no longer accepting applications for the Banting Postdoctoral Fellowships program. Please refer to the Canada Postdoctoral Research Award program web page for information regarding the new harmonized program
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to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories and to develop approaches to predict and monitor