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reliable models and algorithms in these contexts (weakly supervised, semi- or unsupervised learning, domain generalization, active learning, federated learning, privacy preservation, noise and uncertainty
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language processing, large language models, and speech analysis to conduct research on building algorithms for early detection of Alzheimer?s disease based on audio-recorded patient?clinician data. Contribute to prompt
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research activities, assists in preparing human subjects protocols, manages and analyzes data across multiple projects. Contributes to building traditional statistical models and machine learning algorithms
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institutes and centers. The Data and Democracy Research Lab is a unique interdisciplinary team combining expertise in mathematics, algorithm design, geospatial data, and public policy. Members of the lab
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Learning, Theoretical Computer Science (Discrete Mathematics, Algorithms, etc.). Experience with EdTech tools, such as Ed Discussion, Gradescope, GitHub Classroom, Canvas, etc. Ability to respond on short
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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
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5 years research experience in hydrological/agroecosystem modeling. Knowledge, Skills and Abilities Required: Knowledge of agroecosystem modeling, optimization algorithms, and high-performance
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optimization methods: exact methods (MIP/MILP using PuLP) and heuristics (e.g., genetic algorithms) * Solid understanding of statistics, probability theory, data exploration, dimensionality reduction, classical
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/08/2025 END: 31/12/2029 Centre of Principal Researcher: Faculty of Computer Science. Álvaro Leitao Rodríguez PURPOSE OF CONTRACT: Advanced Deep Learning algorithms for solving PDEs and SDEs in finance
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Participates in patient rounds, conferences and committees Actively participates in the development and maintenance of patient management algorithms and standing orders. Documents patient care data in Epic in