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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757
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the delivery of clean energy and industrial decarbonization infrastructure associated with net-zero transitions. The role will report to the Andlinger Center's Dr. Chris Greig, the Theodora D. '78 and William H
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fine tuning and RAG workflows for LLMs on a variety of datasets*Maintain codebases and data pipelines; ensure reproducibility and version control*Work with team members to integrate LLM modules into user
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cancer, the role of nutrient scavenging pathways including autophagy in cancer and host metabolism, growth and survival, metabolic control of the anti-tumor immune response, identification
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH Silvio O
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codebases and data pipelines; ensure reproducibility and version control *Work with team members to integrate LLM modules into user friendly decision support platforms *Facilitate user testing and gather
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both research groups. The Atkinson lab focuses on using protein engineering, electrochemistry, and synthetic biology approaches to control gene expression and metabolism in microbes. The Avalos lab
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-facing materials and first wall concepts for fusion energy devices through surface science experiments. Studies under the controlled conditions of ultrahigh vacuum (UHV) surface science facilities enable