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or application. Strong technical expertise in one or more of the following areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and
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-of-the art in animal breeding, human genomics, ecology and evolutionary biology. The post-doc will thus work with a cross-disciplinary team of researchers and can contribute towards the development of methods
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functional beverage prototypes that are suitable for industry-scale beverage manufacturing and evaluate their emulsion stability and estimated shelf-life. Conduct in vitro bioaccessibility and bioavailability
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areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and Multimodal Models Generative AI, Agentic AI, Physical AI, and
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characteristics Drive to learn new methods and applications Curiosity and creativity in finding problem-related solutions Present and discuss your research with other professionals Engage and contribute
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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on methods, frameworks, and architectures that transform stakeholder information requirements into interoperable semantic models, ontologies, knowledge graphs, and digital twin services. Particular
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with 5+ years experience OR Master's degree with 2+ years experience in Biomedical Engineering, Mechanical Engineering, Electrical / Electronic Engineering, Computer Engineering, HealthTech, MedTech
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an interest in investigating the effects of peatland restoration on hydrology and catchment biogeochemistry by means of a diverse set of methods, including field investigations, modelling and data-driven
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the effects of peatland restoration on hydrology and catchment biogeochemistry by means of a diverse set of methods, including field investigations, modelling and data-driven analyses. Your immediate leader