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technologies, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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Methodology The PhD candidate will develop innovative AI models using machine learning and deep learning frameworks. Methodologies will include supervised and unsupervised learning approaches to identify and
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information and advice on best-practice methodologies in machine learning/deep learning. It is essential that you hold a PhD/DPhil (or close to completion) in a relevant quantitative field (e.g. biostatistics
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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
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PhD project. In addition to electromagnetic geophysics, the candidate is expected to contribute to the development of novel workflows for joint inversion of multiple data types (e.g., borehole acoustic
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Investigator, the Postdoctoral Associate will conduct specialized cardiovascular research techniques and procedures with focus on artificial intelligence and machine learning platforms that will promote
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Summary The Department of Electrical and Computer Engineering (ECE) at Ritchie School of Engineering and Computer Science at the University of Denver is looking to hire adjunct instructors to teach a
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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Professor- Coordinator position to begin January 2, 2026. The Department offers BS and MS, and PhD degrees in Physics. This position is a full-time position with multiple duties. Responsibilities include