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Multi-modal Machine Learning-including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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molecular simulations, and cutting-edge AI techniques including graph neural networks (GNNs) and large language models (LLMs) to accelerate experimental design and discovery of novel materials. The research
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publications. You will work alongside PhD students and interact with experimental partners across the NAP4DIVE consortium. You will have access to the DelftBlue high-performance computing cluster. This position
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Network. https://www.eu4greenfielddata.eu/ ***Double Degree PhD Scholarship in Computer Science Opportunity: "Optimization-simulation coupling for the GHG emission estimation based supervision and
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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. Essential qualifications and experience a PhD (or near completion) in one of the following fields (or a closely related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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/or peer-reviewed journals Required Knowledge, Skills, and Abilities: PhD in Computational Physics, Chemistry, Materials Science, Computer Science/Engineering, Applied Mathematics, or a related field
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large