35 big-data-and-machine-learning-phd Postdoctoral positions at The University of Arizona
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applications. Minimum Qualifications PhD. in Electrical Engineering, Electrical and Computer Engineering, Computer Science, Mechanical Engineering, Communication Engineering, Applied Math, or a closely related
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Sign In Create Profile Postdoctoral Research Associate (Electrical and Computer Engineering) Tucson, AZ, United States | req22541 Apply Now Share Save Job Posted: 5/2/2025 Back to Search
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to work on a project at the intersection of deep learning and computer security/privacy, under the direction of Dr. Michael Wu. The project seeks to investigate security and privacy problems in deep
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, Electrical and Computer Engineering, Computer Science, or a related field of study. Selected applicant must have PhD conferred upon hire. Preferred Qualifications Two years of prior work experience in small
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imbalances. A fundamental understanding of classical Machine Learning Techniques for longitudinal data analysis. An understanding of probability theory and basic frequentist statistical approaches
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related field. Degree must be conferred by start date. Preferred Qualifications Experience with multimodal data integration and machine learning techniques. FLSA Exempt Full Time/Part Time Full Time Number
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innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Plan and lead experiments. Acquire and
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, AND ABILITIES: Strong skills in hydrological modeling and machine learning, Proficient in computer programing (e.g., Python, Fortran, C, Matlab, and/or R), Skills in handling large datasets and high
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PhD in Neuroscience, Psychology, or related fields, and an interest in the neural mechanisms underlying motivated behavioral decision-making. A quantitative background, experience in imaging
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a team. Ability to meet deadlines and manage multiple projects. Data analysis, organization, and problem-solving skills. Minimum Qualifications MD or PhD in Public Health, Epidemiology, Biostatistics