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-edge microscopy method. Job description: We are looking for a student assistant (m/f/d) for the development of deep learning methods for quantum chemistry calculations using quantum Monte Carlo. In
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project - “UAV-based inspection of aircraft with deep learning-based visual inspection system”. Qualifications Applicants should have a higher diploma or a diploma or an equivalent qualification in
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Professor Arbel’s lab in the context of a grant focused on developing multi-modal causal deep learning models to predict future disability progression and treatment response in Multiple Sclerosis
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Research, and Meta. Responsibilities: The Postdoctoral Fellows will be responsible for leading ongoing innovative research projects. Examples include: The development of probabilistic deep learning models
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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science. They should have a track record of or potential for research excellence. They should be enthusiastic about software development and have working knowledge of python and relevant deep-learning libraries (e.g
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opportunities, access to modern GPU clusters for deep learning research, and strong academic-industry connections. CADIA's commitment to open science aligns perfectly with this project's goals of creating
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cohorts, geometric deep learning, computational anatomy, cardiovascular modelling, multimodal datasets. What you’ll need Applicants should have a PhD (or nearing completion) in computational imaging and
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deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows