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of the Wyss Translational AI Catalyst to foster a collaborative community of innovators dedicated to the intersection of Artificial Intelligence (AI), biology, and healthcare. This Fellowship is designed
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to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting
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the fellowship welcomes postdocs from any academic discipline or professional field. Fellowship recipients have included individuals from anthropology, architecture, art history, communications, economics
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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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representative of your work and research interest SEAS is dedicated to building a diverse and welcoming community. Contact Information For more details on our research and recent publications, see the Geometric
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systems or autonomous AI frameworks · Solid foundation in computational biology · Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX) · Strong analytical, problem solving, and communication
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on topics in the science and theory of generative modeling, including (but not limited to): (1) diffusion language models, (2) reward tilting, (3) complexity of score estimation, and (4) sampling with advice
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for communicating scientific ideas. · Strong organizational skills. · The ability to work independently as well as in a collaborative team environment is strongly preferred. · A strong work ethic and a willingness to
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: Computational methods development and consortium data management for the Human Virome Program, with the mandate to characterize viral (phage and eukaryotic) communities across the human body in health and disease
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communication skills. Additional Qualifications Extensive experience with analysis of highthroughput sequencing data and knowledge of bioinformatics tools for sequence alignment, variant calling, sequence data QC