10 machine-learning Fellowship positions at University of Texas at Austin in United States
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, laboratory, and field environments. The degree must have been received within 3 years from the date of application. Preferred Qualifications Familiarity with machine learning (ML) and artificial intelligence
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Computer Science, AI, Networking, or a related discipline within the last 3 years Solid experience with AI/machine learning methodologies, particularly those applicable to network optimization. Proven ability in
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machine learning implementation, and techno-economics. Responsibilities Research Writing Proposal Development Various other duties as assigned Required Qualifications The ideal candidate must have: Ph.D. in
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differentiable programming and physics informed machine learning (Graph Neural Networks and Neural Operators) for solving inverse and optimization problems. Develop AI-accelerated numerical methods for identifying
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research. Capacity to develop machine learning algorithms to increase analytical efficiency. Knowledge of environmental impacts (ecosystems and air quality) of wildland fires and responses to prescribed
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will perform research within the Center for Generative Artificial Intelligence and its parent organization, the Machine Learning Laboratory. Successful candidates will be appointed within the Department
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, neuroscience, engineering, or related discipline within the last 3 years Experience with either transcranial magnetic stimulation, digital signal processing, or machine learning Human subjects’ research
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, Python, R, and machine learning. Salary Range $58,744 + depending on qualifications Working Conditions Uniforms and/or personal protection equipment (furnished) May work around chemical fumes May work
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strong quantitative training in one or more of the following areas: (1) modeling of infectious disease dynamics, (2) statistics, machine learning and AI, (3) operations research and optimization
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the past three years. Strong publication records demonstrated by peer-reviewed journal papers or peer-reviewed conference papers. Experience with machine learning tools and programming languages, including