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Field
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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expertise in deep learning including experience with libraries such as Pytorch Have strong communication, presentation and writing skills; Enjoy working in a multidisciplinary research environment; Are highly
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closely related field. Required Skills : Proficiency in Python/C and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or Keras). Interest in or prior experience with
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to the academic environment through teaching and supervision activities. If you enjoy combining deep scientific questions with computational innovation—and want your work to support the future of sustainable
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variational models and deep learning techniques. You will implement and validate reconstruction algorithms, ensuring their performance, robustness, and efficiency for clinical application. You will participate
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will provide deep, high-resolution near-infrared imaging of far more area than ever before possible. Roman’s launch is expected in the fall of 2026, making this project well timed for delivering
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, CIKM WWW, ISWC, VLDB) Have excellent programming skills; Established expertise in deep learning including experience with libraries such as Pytorch Have strong communication, presentation and writing
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, analysis and deep learning, 2) biostatistics and health/clinical data analysis or 3) cellular and molecular techniques will be an advantage. Opportunities for publication and independent development will be
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Monte Carlo, neural quantum states, tensor networks, machine learning and data science, dynamical mean field theory, diagrammatic Monte Carlo, etc.) Key Responsibilities Conduct independent and
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TAMU. Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment. Knowledge of characteristics associated with mild cognitive