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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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eligible employees. Please see this link for more information. 0.00 Yes No No Review No $15.49 Minimum Hourly Rate Join our Talent Network to receive updates about working at Princeton. Princeton
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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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. Please see this link for more information. 0.00 Yes No N/A No No No #LI-LO1 $15.49 Minimum Hourly Rate Join our Talent Network to receive updates about working at Princeton. Princeton University job
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social networks and their physical and social environment receive information and cues from those sources as well as feedback from the effect of their decisions. The BSPL puts a special emphasis on
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Rate Join our Talent Network to receive updates about working at Princeton. Princeton University job offers are contingent upon the candidate’s successful completion of a background check, reference
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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