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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge
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high quality and robust integration. The PhD is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do Your tasks and
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are looking for a PhD candidate to research new adaptative architectures and foundation models for the integration of healthcare data specifically incorporating patient preferences. This includes challenges
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within trusted digital environments. Their research focuses on ontology-driven conceptual modelling, FAIR data stewardship, and model-driven system/service engineering, dealing with data-driven services
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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; You have a good team spirit and like to work in an interdisciplinary and internationally oriented environment. You are proficient in English. Additional Information Benefits As a PhD candidate at UT
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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enriched with additional time and scale dimensions for dynamic, space- and time-adaptive simulations. Managing this n-dimensional data efficiently is a central challenge. In your PhD research, you will
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initiates new and internationally oriented PhD research projects focusing on pioneering and innovative research in the fields of management and business research. For more information about ERIM please visit
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models. by combining cutting-edge data science with advanced clinical expertise and imaging technologies. Your colleagues: A dynamic, interdisciplinary team of intensivists, clinical technologists, PhD