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assistant professor or associate professor whose research advances parallel and high-performance computing. Relevant areas include computer architecture, operating systems, compilers and the
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HPC concepts, including parallel computing, distributed systems, and optimization. Analytical skills, problem-solving abilities, and a growth mindset. Additional Qualifications Applicants should be
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performance and funding. Resources for research expenses including publication charges, related conference travel, workshops, and computing resources will be available. Further information about the BHI may
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numerical astrophysics. The successful candidate will have access to our new computing facilities and will have the opportunity to interact and work with researchers in both the Harvard College Observatory
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( https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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( https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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models of brain development and neurodevelopmental disorders. This person will apply and develop computational methods to analyze datasets of varying modalities, such as RNA -seq, ATAC -seq, and
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-time Postdoctoral Research Fellow to join the causal inference team supervised by Professor Francesca Dominici. The position will focus on developing and applying novel causal inference methods for
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) and foundation models for biomedical research Electronic Health Record (EHR) analytics and clinical data integration Biomedical image analysis and quantitative microscopy High-performance computing
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) and the Martinos Center for Biomedical Imaging (Harvard/ MIT /Mass General). In parallel, there will be opportunities to analyze and publish existing data upon identifying areas of mutual interest