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Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model
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problems, statistical learning and machine learning (machine learning, deep learning) - Knowledge of associated software development tools and environments: Python, PyTorch, Scikit-learn, Jax, Julia
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date specified in AP Recruit to learn whether the department is currently reviewing applications for a specific position. If there is no future review date specified, your application may not be
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demonstrated track record in protein structure modelling methods, with hands‑on experience in protein or biologics design and engineering. Hands‑on experience with common machine learning / deep learning
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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of Programmable and Intelligent Networks Position You will work actively on the preparation and defence of a PhD thesis Edge Intelligence for 6G Networks. The PhD project will deep dive into Edge Intelligence
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Praha 120 00, Czechia [map ] Subject Areas: Statistics, data analysis, information theory, machine learning, deep learning, and data science Appl Deadline: 2026/04/16 04:59 AM UnitedKingdomTime (posted
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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, deep learning, and cognitive psychology and ergonomics. The EnACA project consortium includes the Computer Science, Image, and Interaction Laboratory (L3I/EA2118, University La Rochelle), the Fundamental
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg