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or more senior research positions to analyze and model the delivery of clean energy and industrial decarbonization infrastructure associated with net-zero transitions. The role will report to the Andlinger
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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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(energy auditing, GHG accounting, resource recovery)*Strong publication record and excellent written/verbal communication skills*Experience in coding for high performance computing (e.g., university cluster
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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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publication record and excellent written/verbal communication skills *Experience in coding for high performance computing (e.g., university cluster or similar systems) is desired The term of appointment is
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of laminar/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
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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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. Conte Center on the "Cognitive Thalamus". The successful
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values in collective behaviors (e.g., in online social networks). The proposed research is expected to yield both theoretical and empirical publications. The candidate will be appointed in the Department