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. Knowledge of data analysis, optimization, and machine learning techniques is a plus. Knowledge of machine learning libraries (e.g., PyTorch or TensorFlow), SDR hardware (e.g., USRP) and software (e.g
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with one of the following doctoral research projects. 1. AI-Aided Site Reconnaissance and Rapid Assessments for Settlement Upgrading How can spatial analytics, remote sensing, and machine learning models
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stays at foreign educational institutions Support to education activities in courses within the Software Engineering area Other career-promoting work, such as learning grant preparation fundamentals Be
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) with computational methods. The candidate will obtain single-molecule multiplexing data and validate machine learning predictions using the high-throughput data. The successful candidate will collaborate
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discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we
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evaluation strategies. In close collaboration with chemists, engineers and data scientists, a platform is being developed that combines materials development, process optimisation and machine learning
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Are you fascinated by how curiosity shapes learning in the classroom? Would you like to investigate how children seek information, explore and learn in real-world educational settings? If so, then
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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analysis. • Experience with, or a strong interest in, machine learning, probabilistic modelling, statistics, signal processing, digital health or wearable sensor technologies. • Programming
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and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please