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Field
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AI/ML, with a focus on multimodal learning, computer vision, and scientific machine learning Develop novel algorithms and architectures for tasks such as multimodal retrieval, reasoning over complex
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through
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theoretical analysis, including stability estimates and convergence proofs, to guarantee the reliability of the developed algorithms. Design and execute high-fidelity numerical simulations for PDE-based models
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Intelligence (AI) approaches and methods with the long-term objective of improving clinical cancer care. The training, project development, and application will be mentored by Dr. Peter Nelson and Dr. Jeff Leek
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practice of imaging, cardiac mapping and targeted radiation therapy Create, develop and experimentally and clinically implement mechanistic and AI based algorithms Support the acquisition and analysis
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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produce software implementations of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
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description languages. Develop and optimize EDA workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single