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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data
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processing, artificial intelligence, cognition and deep learning, machine learning, navigation and mapping, autonomous driving, assistive robotics, drones, dynamics and vibration, acoustics, medical imaging
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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, or behavioral data) and be proficient in Python and modern deep-learning frameworks (ideally PyTorch). Experience in computer vision, multimodal data fusion, self-supervised or generative modeling is highly
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Research Framework Programme? Not funded by a EU programme Reference Number EU-59005 Is the Job related to staff position within a Research Infrastructure? No Offer Description AI and Deep Learning
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: Design and implement ML, deep learning, and Large Language Models for orthopaedic applications Work with multimodal clinical data, including: Medical imaging (X-ray, CT, MRI) Electronic health records (HER
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The expected pay for this position is $70,000 per year + benefits. AI and Deep Learning for Genomics, Transcriptomics, and Bioinformatics Job Summary The School of Biomedical Engineering at the University
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the results, and apply the models in clinical environment. The incumbent’s responsibilities include: Design and implement ML, deep learning, and Large Language Models for orthopaedic applications Work with
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cross encoder architectures and retrieval augmented generation. Strong programming skills in Python and deep learning frameworks, familiarity with MLOps practices, data governance for sensitive health
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data