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technologies; and applies these methods to study regulatory genomics of cell function and cell-cell interactions, with a focus on immunology and cancer. The successful candidate will have an opportunity to lead
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independently while working well in an interactive and dynamic setting. This position is subject to the University's background check policy. The work location for this position is in-person on campus
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. Conte Center on the "Cognitive Thalamus". The successful candidate will be part of a diverse team of experimentalists, theoreticians and biostatisticians that studies thalamocortical interactions in
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methods to human-environment questions*Excellent academic writing and communication skills in English*Strong publication record (relative to degree timing)*Collaborative spirit in interacting with
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*Strong publication record (relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM
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evolutionary biology, ecology, zoology, paleobiology or a related field. *Excellent writing ability in English. *Creativity and the desire to work in an interactive and inter-disciplinary environment. A solid
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but not required. Excellent writing ability in English is essential as well as creativity, energy, and the desire to work in an interactive and inter-disciplinary environment. The Term of appointment is
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forms of electronic and magnetic structure theory and calculations is also expected. The successful candidate will have a strong research and publication record and must have a Ph.D in physics or related
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candidate will be part of a diverse team of experimentalists, theoreticians and biostatisticians that studies thalamocortical interactions in different brain models (tree shrew, macaque, human neurotypical
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757). When applied online to global ice-ocean simulations, this neural network substantially improves sea ice simulation