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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary geospatial or remotely sensed data. Quantifying uncertainty and correcting
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evaluate them alongside newly developed approaches. Integrating methods such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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. He/she/they will learn and apply state-of-the-art molecular and cell biology technologies established in our team, ranging from in vivo disease models to multi-omics and single cell analysis
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at the Institute for Computing and Information Sciences (iCIS), part of the Faculty of Science at Radboud University . The Data Science Group comprises around 50 researchers with expertise in machine learning
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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of visualization and multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240
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generalizability, reliability, and robustness. Prof. Li has authored over 40 papers in top-tier AI and machine learning conferences and journals. Ranked among the Top 50 researchers in “Spatiotemporal Data Mining