71 advance-soil-structure-modeling Postdoctoral research jobs at Princeton University
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polymer physics. The successful candidate will develop strategies to design, synthesize, and characterize the properties of soft materials using advanced microscopy techniques and related methods
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opportunity to engage in cutting-edge interdisciplinary research focused on Generative AI within the context of construction robotics, working under the guidance of Dr. Arash Adel, Assistant Professor in
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, investigating (a) cumulative environmental impacts, (b) the use of census microdata for social vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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advanced microscopy techniques and related methods. Candidates who are nearing completion of their Ph.D. (i.e. with a confirmed defense date) or hold a Ph.D. in chemical engineering, chemistry, materials
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position for new projects to characterize synthesis processes and novel materials in several research thrusts: i) development of advanced manufacturing processes for low-cost battery cathode active materials
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The Ghanim lab is seeking a postdoctoral candidate or more senior researcher to study macromolecular complexes involved in LINE-1 retrotransposition using an integrated biochemical and structural
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on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to advance the use of mathematical and statistical models
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, cell biology, structural biology, microbiology, developmental biology, virology, genetics and cancer biology. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year
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vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda of this research is assessing the fitness of geospatial indicators to inform conceptual and policy