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Position Details Position Information Recruitment/Posting Title Postdoctoral Associate Job Category Staff & Executive - Research (Laboratory/Non-Laboratory) Department CINJ - Guo Laboratory Overview
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Carnegie Mellon University, Institute for Computer-Aided Reasoning in Mathematics Position ID: 3637-PF [#27988] Position Title: Position Type: Postdoctoral Position Location: Pittsburgh
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Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and
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: Education: Ph.D. in machine learning, computer science, engineering, physical science or related technical discipline. Experience: Expertise in developing and training AI models Proficiency in Python
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focusing on the integration of machine learning, wafer-scale synthesis of materials. The role will contribute to the university's research mission by conducting fundamental research, helping secure external
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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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opportunity to field test and validate their methods using real-world systems. Postdoctoral fellows will work across the following research areas: Predictive machine learning Robust and stochastic optimization
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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assimilation, machine learning, and seasonal weather forecasts. As a Postdoctoral Research Fellow, you will play a crucial role in developing and testing statistical models for the accurate forecasting