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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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. This may involve techniques such as spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint
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-edge field of Human-Centered AI Technologies using advanced Generative AI and novel interaction technologies such as VR/AR and Eye Tracking. Potential Project Ideas are: 1. Multimodal Machine Learning
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make buildings smarter and more sustainable? Join us to advance your career by working
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for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated expertise in
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via autophagy and lysosomal targeting in learning and memory and disease models using rodents and iPSC-derived cell cultures. These mechanisms will be investigated in both healthy conditions and
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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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of the cells into tumours and lead to improved tumour killing. To be successful you will need: A PhD in immunology and cancer biology, specifically in CAR-T cell therapy and chemokine biology. Demonstrated