82 algorithm-development-"Newcastle-University"-"Newcastle-University" Postdoctoral positions at Princeton University
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: 278599539 Position: Postdoctoral Research Associate/Research Program in Development Economics (RPDE) Description: The Research Program in Development Economics (RPDE) at Princeton University's School
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The Research Program in Development Economics (RPDE) at Princeton University's School of Public and International Affairs invites applications for two Postdoctoral Research Associate positions
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, Atmospheric and Oceanic Sciences, Geosciences, Computational Science and Engineering, or a related area is required.The position will involve developing models and algorithms for the evolution of inorganic
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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, 2026) in Psychology with demonstrated expertise in gender development. Applicants should have expertise in video coding (e.g., Datavyu), longitudinal data analysis (e.g., RI-CLPM, growth-curve analysis
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degree (or expect to receive a PhD degree by June 15, 2026) in Psychology with demonstrated expertise in gender development. Applicants should have expertise in video coding (e.g., Datavyu), longitudinal
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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-microenvironment interactions during cancer progression. Ludwig Princeton Branch is dedicated to accelerating the study of metabolic phenomena associated with cancer to develop new paradigms for cancer prevention
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) with expertise and interest in Large Language Models (LLM) for Energy Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune
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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