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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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, including but not limited to cement chemistry, material science, or structural materials and mechanics. Candidates with a strong commitment to interdisciplinary research are especially encouraged to apply
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include designing online studies for peer interaction with children, writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers in the group. The term of appointment is
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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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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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. 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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Qualifications: Ph.D. degree in 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
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-modal single-cell, spatial and genome editing technologies; and applies these methods to study regulatory genomics of cell function and cell-cell interactions, with a focus on immunology and cancer