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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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with a desire to research and learn more about biomedical research, multi-omic integration analytics and machine learning. In this role you will produce highly impactful biomedical informatics research
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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sociology. Strong quantitative skills and experience with large-scale data analysis required. Computer Science/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related
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integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging,” and we love
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
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. Salary and Benefits: This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found