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and teaching activities. Engage actively with new educational models and embrace innovative, interactive, technology-enhanced learning, teaching, and assessment approaches; understand and have an
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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appropriate computer language/tools to provide technical solutions for highly complex application development tasks. Write functional/technical specifications from the highly complex system requirements
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of artificial intelligence models, including machine learning and deep learning; c) Immediate availability to start the scholarship (to be stated in the motivation letter); d) Proficiency in the English language
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the opportunity to work at the intersection of AI and health sciences, focusing on developing machine learning approaches to diagnosing musculoskeletal pain conditions, including low back pain and osteoarthritis
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, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal
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research agenda using advanced quantitative methods—such as machine learning, computational modeling, big-data analytics, and wearable technologies—to study tourism, hospitality, and/or human performance
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from Hi-C and Capture Hi-C experiments. Have experience developing graphical user interfaces (GUIs). Candidates with knowledge or experience in machine learning methods will be prioritized. Successful
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development in topics such as computer vision, audio signal processing, machine learning, deep learning, and/or sensor systems. Experience in collaboration and technology transfer to partners outside