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school, with skills in numerical analysis, signal analysis, programming (C++, python), and machine learning. The candidate must be motivated by biomedical engineering, and physiological knowledge, although
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Skills/Qualifications Academic background: Bachelor's Degree in Telecommunication Engineering, Computer Engineering, Biomedical Engineering, Industrial Engineering, Aeronautical Engineering or other
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, integrating machine learning and physiological computational models (patient digital twin) to: 1) combine physiological knowledge and clinical data; 2) improve model interpretability; and 3) minimize
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. ESAT of KU Leuven (Belgium). The goal of this research is to develop new machine learning methods for the quality assessment and enhancement of signals and annotations in time series data, with
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Skills/Qualifications Academic background: Bachelor's Degree in Telecommunication Engineering, Computer Engineering, Biomedical Engineering, Industrial Engineering, Aeronautical Engineering or other
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Framework Programme? Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Digital Health & Biomedical Engineering Location: Highfield
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will be part of the Facial and Cranial Anomalies Research Group led by Prof. Dr. Dr. Andreas Müller PhD, MHBA, in affiliation with the Department of Biomedical Engineering and Department of Clinical
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-solving skills, and the ability to work collaboratively in a team are expected. We imagine that the successful candidate will have a PhD in neuroscience, medicine, biomedical engineering, physiotherapy
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Biomedical Engineering, Computer Science, Electrical Engineering or related field and a demonstrable record of accomplishment in medical image analysis, organ-specific imaging, computer vision, and image
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The successful candidate will preferably have a PhD in Physics, Chemometrics, Informatics, Chemistry, or related Engineering field and experience in the following skills: • Machine learning and data analysis based