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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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outreach to other school districts in the lab’s network interested in taking a socio-technical approach to assigning educational resources. Candidates will be evaluated according to their: Scientific record
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you would be a great fit for the Stanford Energy Postdoctoral Fellowship. How will you leverage the training, network, resources, and support of this fellowship program to impact the energy field? What
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uniquely cross‑disciplinary team and work closely a network of collaborators. • Jan Zimmermann — University of Minnesota • Aaron Batista — University of Pittsburgh • Kimberly Stachenfeld — Columbia