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Field
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational
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’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. The Department of Women and Children’s Health is a lively and supportive
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Location: Luxembourg, Luxembourg 1511, Luxembourg [map ] Subject Area: Quantum LDPC codes with efficient decoding algorithms Appl Deadline: none (posted 2025/08/05) Position Description: Apply Position
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Iterative Algorithms: Optimization and Control.” About the Project The focus of the project is the analysis of iterative algorithms arising from time discretizations of nonlinear evolutions of various kinds
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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, virtual assistants, or AI-driven systems such as chatbots, recommender algorithms, or generative AI. The position focuses on how communicative processes are shaped by and shape these technologies
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of Business, Economics and Statistics at the University of Vienna invites applications for a Tenure-Track Professorship in Computational Statistics and Data Analysis The position We welcome applications from
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required to make data driven discoveries that increase our scientific knowledge and improve the quality of life. We architect ecosystems of large-scale commons of research data, computing resources