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microscopy systems that integrate machine learning, robotic control, and real-time data analysis to achieve autonomous imaging and interpretation of complex materials systems. The Fellow will design 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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intelligence that coordinates the entire experimental ecosystem. The Postdoctoral Fellow will develop agentic AI models and frameworks for intelligent experimental workflows, which couple machine learning, real
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the last three years. Solid experience with AI/machine learning methodologies, particularly those applicable to network optimization. Proven ability in programming and familiarity with network simulation
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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areas such as data analysis, statistical modeling, machine learning, numerical modeling, or remote sensing Preferred Qualifications A general understanding of ecosystem modeling or ocean circulation
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one or more of the following areas: (1) modeling of infectious disease dynamics, (2) statistics, machine learning, and AI, or (3) operations research and optimization. Preference will be given
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computational cluster and/or high-performance computer with Linux OS. Excellent oral and written communication skills and a collaborative working mindset. Strong publication record in closely related research
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from date of hire. Preferred Qualifications Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as
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have been received within the last three years, 1 year of experience with machine learning, natural language processing, AI tools and frameworks, data integration, and/or explainable AI. Proficiency in