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postdoctoral fellowship in the Arlotta lab involves computational analysis of large, multimodal single-cell datasets, as part of a collaborative project which also aims to generate AI and machine learning
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deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific
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in modern machine learning and a strong record of research accomplishment who are excited to build brain foundation models and other AI systems that advance our understanding of neural activity, brain
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health risks and adaptation strategies. Duties and Responsibilities Design, implement, and evaluate deep learning models for spatiotemporal data, with an emphasis on medium-scale foundation models
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establish a physical laboratory research program at both institutes. We seek to recruit a computational researcher with expertise in machine learning and mathematical modelling whose work addresses
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establish a physical laboratory research program at both institutes. We seek to recruit a computational researcher with expertise in machine learning and mathematical modelling whose work addresses
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will work closely with Kempner faculty, researchers, and students on foundational machine learning and biologically informed scientific applications. The position is particularly well-suited to
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Performance Computing are desirable. We particularly encourage applicants with expertise in Multi-scale Modeling, Evolutionary Computation, Diffusion models, Reinforcement Learning . The successful candidate
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inference and machine learning to estimate the excess number of adverse health events and directly attributable to data centers ● Develop a decision-support platform that allows data center expansion while
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approaches for verified programming. Additionally, there would be opportunities to apply the work in precision medicine. Core Responsibilities: Conduct independent and collaborative research. Disseminate