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, anticipates offering a number of postdoctoral or more senior research positions in theory, observation and instrumentation, including (but not limited to): the Lyman Spitzer, Jr. Postdoctoral Fellowship
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. The successful candidate will be expected to assist with the commissioning of a new shock tube facility and will conduct fundamental experimental research related to multiple ongoing projects, including
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
models, and their coupling, using machine learning. The postdoc will be expected to collaborate with other postdocs at Princeton and with other members of the M2LInES project across multiple institutions
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. The researcher will work with a group of interdisciplinary scholars across multiple institutions that includes Elke Weber and Chris Greig at Princeton University, Sara Constantino at Stanford University, and Holly
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simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar/neuropixel probes and electrical microstimulation to study
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
at Princeton and with other members of the M2LInES project across multiple institutions. In addition to a quantitative background, the selected candidates will ideally have one or more of the following
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positions in theory, observation and instrumentation, including (but not limited to): the Lyman Spitzer, Jr. Postdoctoral Fellowship; the Henry Norris Russell Postdoctoral Fellowship; the Joint Carnegie
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, molecular biology, microbiology, biochemistry, biophysics, computational modeling or related fields. Experience in metabolic engineering, synthetic biology, yeast genetics, or control theory is a plus but not
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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application