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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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-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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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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) 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
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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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effort developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental
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detailed information on type, size, location of data centers in the US, their electricity and water demand, carbon emissions; exposure to air pollution. ● Develop and/or apply methods for causal