27 machine-learning-"https:"-"https:"-"https:"-"https:" research jobs at University of Texas at Austin
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requirements. Demonstrated detail orientation, ability to follow-through, and strong problem-solving skills. Proficiency in Microsoft Excel and Word and willingness to learn other technologies as necessary
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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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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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, or computational methods Strong organizational skills and ability to manage multiple projects independently Preferred Qualifications Interest and/or experience with large-scale natural language processing, machine
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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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experience in human cognition, particularly episodic memory or emotional cognition, and/or cognitive aging research Experience in advanced neuroimaging and computational analyses (i.e. machine learning methods
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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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, dissolved pore water components, nutrients, chlorophyll, TSS, CHN and isotopic analysis, sediment grain size, and algal epiphyte enumeration and identification. Computer data entry, data QA/QC, some basic and
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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