53 big-data-and-machine-learning-phd Postdoctoral positions at The University of Arizona
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Qualifications PhD in Robotics, Electrical & Computer Engineering, Mechanical Engineering, Biomedical Engineering, Computer Science, or closely related field. Must have PhD conferred upon hire. Preferred
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Sign In Create Profile Postdoctoral Research Associate, Electrical and Computer Engineering Tucson, AZ, United States | req24106 Apply Now Share Save Job Posted on: 10/6/2025 Back to Search
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at the field, drone, and satellite scale. Big data analysis including processing and analyzing EMIT hyperspectral datacubes over large spatial domains such as the Colorado Plateau and even global. Presenting
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, demonstrated by a strong publication record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or
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record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or MD/PhD degree, and be self
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University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here . Duties
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& Responsibilities Developing automated manufacturability analysis methods for additive and conventional manufacturing processes. Applying machine learning techniques to 3D engineering data (CAD models, meshes, voxels
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evaluation of alloys; familiarity with finite element methods. Skills and experience in programming, machine learning, or signal processing are all considered a plus. Outstanding UA benefits include health
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related fields. Skilled in operating and troubleshooting trace gas analyzers, sensors, and/or automated sampling equipment. Ability to analyze time series data (or reasonably learn) using scientific
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projects in AI-driven GNC for space robotics systems, leveraging both classical optimization techniques and modern machine learning methods. Lead and support research projects in AI-driven solutions for SDA