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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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innovative material solutions. This project tackles this challenge head-on. The project vision is to develop a pioneering AI-driven methodology for designing Functionally Graded Materials (FGMs) specifically
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Three postdoctoral positions at the King Abdullah University of Science and Technology (KAUST) under the mentorship of Prof. Jürgen Schmidhuber.This project, located at the intersection
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generation data-driven stochastic and distributionally robust optimization methodologies or (ii) develop advanced fairness promoting stochastic optimization frameworks. In coordination with Prof. Shehadeh
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Prof Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This research project focuses on the development of methods for intelligent wildfire detection and localisation
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scraping, and other proprietary techniques. Develop, test, and evaluate algorithms and software, including Large Language Models, to analyze social media data, with a focus on the volume, content
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently
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, uncertainty quantification, transport, financial markets, etc. Here, it is important that research in algorithm development has strong connections to needs in an application state space. Area 2: Methods
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collaboration with Prof. Giovanna Tinetti and her team and collaborators at KCL. The main purpose of this role is to develop new and/or to use existing models to simulate the atmospheres of exoplanets and use