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are essential Additional qualifications Experience and courses in one or more subjects are valued: statistical machine learning, optimization, deep learning and signal processing. Rules governing PhD students
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E-mail jakub.ceranka@vub.be Website https://jobs.vub.be/job/Elsene-PhD-in-'medical-image-analysis-and-artificial-in… Requirements Research FieldEngineering » Biomedical engineeringEducation
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the long term. Is Your profile described below? Are you our future colleague? Apply now! Education PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote
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) and define the problem mathematically. Secondly, a central component of the PhD will be to learn mappings between heterogeneous spaces through latent-variable models and representation learning. Some
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for supply chain and marketing optimization. The project will integrate machine learning, deep learning, foundation models, and interpretable AI approaches, ensuring scalability, robustness, and industrial
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evaluate innovative methods based on generative models and Vision-Language Models. Design, implement, and validate deep learning approaches for vision applications. Publish research results in leading
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/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in
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the competent authority of the Ministry of Higher Education, Research and Innovation (MESR). "Video content security in a deep learning coding architecture" Over the past few decades, numerous video compression