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involves building and training deep-learning models for TEM image reconstruction and interpretation, linking image features to local chemistry, defects, and dynamic transformations under varying
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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-postdocs/fellowships/jill-hruby-fellowship/ If invited for interview, you will be assigned a Sandia mentor and required to submit a full research proposal prior to your interview Interviews are tentatively
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. Key deliverables include developing ‘storylines’ for low-likelihood high-impact volcanic eruptions and performing volcanic climate-model simulations. WP2: Past Volcanic Climate Shocks – 500s–600s and
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
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, simulation, prototyping, and pre-clinical validation of a novel temperature-insensitive, 6-degree-of-freedom force sensor for use in minimally invasive cardiac surgical instruments. This patented technology