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; Familiarity with machine learning concepts and large language models. Deep expertise is not required, but candidates should be comfortable engaging with these technologies at a foundational level; Knowledge of
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monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
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Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record of publications - Excellent communication skills and ability to work in a fast
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Research Description The project aims at combining three primary data sets (JWST NEXUS spectroscopy, Euclid Deep Field North
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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in
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. Experience with deep learning and programming, preferably in Python, are required and should be evident from your academic track record, including the (online) courses you've followed, your publications
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. in Computer Science or a closely related field, with research focus in Reinforcement Learning, Machine Learning, Embodied AI, or AI for Education. Strong background in deep reinforcement learning, with
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their valuable contributions and deep connection to country and pay respect to Elders past and present. Advance internationally recognised Antarctic climate and palaeoclimate research Be part of nationally funded
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or deep learning reconstructions). Knowledge of radial data acquisition strategies, artifact mitigation methods, and their use in parametric imaging (e.g., T1/T2/T2* mapping). Preferred Qualifications
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and