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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about advancing Machine Learning by integrating
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contribute to the development of innovative, physiology/ machine learning-driven clinical solutions and decision support tools for critically ill patients, focusing on cardiovascular and respiratory monitoring
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Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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systems increasingly provide personalized recommendations in domains such as nutrition and lifestyle. However, many recommender and prediction systems rely heavily on opaque machine learning techniques
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degree in AI, Computing Science, Mathematics, or Data Science. Strong coding, communication and organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch
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within the field of machine learning, search, and reasoning techniques. Demonstrable knowledge and/or experience in algorithms and programming is a must; Is able to translate and convert this knowledge
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, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models. The postdoctoral researcher will be responsible for: Developing a
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evaluation of multi-disease tests, and test this using AI applications in radiology as a practical case study. Where to apply Website https://www.academictransfer.com/en/jobs/360280/phd-position-developing