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positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts . Additional details will be discussed during the interview process. Certain
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statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration
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in internal meetings and at national/international conferences. ● Collaborate with an interdisciplinary team (bio)statisticians, data scientists, computer scientists, and climate scientists
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and at national/international conferences. Collaborate with an interdisciplinary team of biostatisticians, computer scientists, and climate scientists. Contribute to open-source code, reproducible
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and at national/international conferences. ● Collaborate with an interdisciplinary team of biostatisticians, computer scientists, climate scientists and community and industry partners. ● Contribute
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research environment and communicate technical work clearly. Additional Qualifications Experience with foundation model training, post-training, adaptation, or evaluation Experience with agentic workflows
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recordings. Experience with large-scale datasets, distributed training, or high-performance computing environments. Experience with foundation model training, post-training, adaptation, or evaluation
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Qualifications Experience with foundation model training, post-training, adaptation, or evaluation. Experience with protein structure modeling, protein–protein docking, or small-molecule–protein docking
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systems, cosmic-ray detectors, and data analysis are strongly encouraged to apply, as these skills will be preferred in the selection process. This appointment duration is for up to three years, with