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postdoctoral scientific training. 7+ years of work experience. Qualifications PhD required. Ability to learn safety data analytics, perform literature reviews, strategize and write, support team projects
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, MATLAB, and/or C++/C#) Knowledge of machine learning techniques, particularly for time-series data Background in prosthetics or human-machine interfaces is advantageous PhD Stipend 2: Adaptive Control
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 6 hours ago
-based and institutional offices. · Teach courses for students in both the PhD program and other programs in the university. · Collaborate and create supportive partnerships both within and
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evolutionary analysis. A central component of the research will be to develop machine learning and deep learning methods trained on coding sequences and protein structure to extract patterns in data and to draw
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the largest optical telescope in the world and will develop skills in machine learning, observational and theoretical astrophysics. For more information on this project please contact s.littlefair
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encompassing econometric and statistical models, simulations, and machine learning and deep learning methods. Support senior staff with cross-cutting research efforts; Mentor junior OFRA staff; Clearly champion
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of data from in-Situ AM Process Monitoring tools, machine agnostic algorithms will be generated for quality control. Knowledge transfer of the methods developed onto industrial machine platforms will be a
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/ machine learning methods, and 10% on administrative and leader tasks. The post is with tenure and permanent. OCBE wishes to strengthen its capacity in machine learning and is looking for candidates with
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associate beginning August 16, 2025. The department seeks an individual with the credentials to teach undergraduate courses in recreation and sport management; specifically, leisure, recreation and wellness
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, advanced statistical methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and