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) a PhD in a quantitative discipline such as computer science, mathematics, statistics, engineering, or a related field. Strong programming skills and experience in machine learning or statistical
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or experimental research involving passive, active, specialty, or telecommunication optical fibers, or in modeling linear and nonlinear phenomena—including the use of deep learning methods—in the field of optical
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yrs. of experience in field or PhD in field of expertise + 0-2 yrs. of experience in field Research Specialist, Psychometrics & Machine Learning Applications: $67,150 - $83,900; Master's in field
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lifetime. Most studies on this topic explore optimization and deep learning methods for finding the global optimal solutions offline and verify the results by model-in-the-loop simulations, but this project
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for REF 2021 - Research Excellence Framework. For more information about our research results and case studies please visit the following link: https://www.exeter.ac.uk/research/ref2021/ Projects Available
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(Taicang) nationally and internationally. Responsibilities and Duties We are looking for future colleagues in all fields of computer science, data science, artificial intelligence, machine learning, deep
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
languages) # Knowledge of modern deep learning frameworks (e.g. pyTorch, Tensor-flow, Jax, ...) # Experience working in Linux shell/cluster environment and on shared resources # Experience of collaborative
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Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
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lightweight deep learning model for welding defect recognition. Weld. World. https://doi.org/10.1007/s40194-024-01759-9 3. J. Franke, F. Heinrich, R.T. Reisch, “Vision based process monitoring in wire arc
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cardiometabolic disease. This two-year position (with the wish and possibility of extension for another four years) is ideal for a scientist with deep technical expertise and passion of alleviating disease burden