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Computational Astrochemistry/Algorithm development for Quantum Dynamics Calculations School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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algorithm and framework; (b) collect data, analyse and prepare report; and (c) perform any other duties as assigned by the project leader, the Head of Unit or their delegates. Qualifications Applicants
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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design using brute force methods by using non-discriminate parameter variations and recently innovative approaches using artificial neural networks (ANNs) are also developed for the prediction
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data preprocessing, algorithm development, and optimization techniques. Excellent communication skills in English. Prior experience with environmental or photocatalytic systems is a plus. A fully funded
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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to contribute to cutting-edge research in robot intelligence, machine learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms
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Local Rules for Kolmogorov–Arnold Networks (KANs) School of Computer Science PhD Research Project Directly Funded Students Worldwide Prof Eleni Vasilaki Application Deadline: Applications accepted
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”. They will be required to: (a) assist in coding tasks related to the implementation of algorithms for energy system optimisation; (b) collect data, analyse and prepare report; and (c) perform any