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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. Start date: Fall 2026 Duration: The appointment is for 3 years It is
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junior developers and researchers Stay current with the latest developments in Deep Learning frameworks for weather forecasting and climate science. Where to apply Website https://jobs.fbk.eu/Annunci
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programming skills in Python or C++, and practical experience with deep learning libraries (e.g., PyTorch) Desirable criteria 1. Research experience in one or more of the following areas: tactile sensing
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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advanced analytical and statistical techniques to extract actionable insights from complex datasets. Train, evaluate, and continuously refine deep learning and machine learning models, prioritising
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is