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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 1 month ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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(with the potential to be extended) with the Alabama Center for the Advancement of Artificial Intelligence. Leads the forefront of research in artificial intelligence, machine learning, and data science
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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking
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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and