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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting Models Basic Qualifications A Ph.D. or equivalent degree
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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting Models Basic Qualifications A Ph.D. or equivalent degree
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interdisciplinary approaches that combine advanced microscopy (confocal, electron, in vivo multi-photon), viral vectors, protein engineering, mouse models, and multi-omics analyses. For further information on the lab
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to candidates with prior experience in one or more of the following areas: ecological (population) modeling, geographic information science, comparative genomics, chronobiology, insect rearing, and/or ecological
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screening (e.g., CRISPR-based or related screening approaches), viral infection models, and insect or arthropod cell culture systems. The successful candidate will work with Norbert Perrimon to develop and
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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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 data. Our team
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multi-photon), viral vectors, protein engineering, mouse models, and multi-omics analyses. For further information on the lab, please visit: www.shigroup.org We welcome applications from postdoctoral
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position in the Gozzi Lab at the Rowland Institute at Harvard (https://www.rowland.harvard.edu/). Our lab’s primary focus is on bacterial-encoded domesticated viruses, known as gene transfer agents
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outstanding research in computational physics for modeling of complex physical phenomena. Additional Qualifications Candidates must have experience in carrying out large-scale computational modeling of complex