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Field
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offer a PhD student position at the Universitat de Barcelona (as part of the PhD Program in Mathematics and Computer Science) to develop new AI and federated learning algorithms for diagnostic imaging in
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these data structures and their associated algorithms to enable pattern-matching and other operations required, for instance, to infer microbial transcriptional regulatory networks through comparative genomics
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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y 6g. ----------------------------- Support in research studies and development of prototypes for confidentiality and secure authentication using quantum resistant asymmetric algorithms. Application
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learning algorithms, and others, as well as related research in other projects of the CBA-N3Cat group. -Direct the writing of articles and possible dissemination activities related to the different quantum
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. Obtain and process satellite image databases at a global level. Programming deep learning and signal processing algorithms and conducting tests. Write and present new project proposals. Organize meetings
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), machine learning algorithms (reinforcement learning), and/or explainability techniques. LanguagesENGLISHLevelGood LanguagesSPANISHLevelGood Additional Information Benefits 1.255 €/monthly gross salary
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their creation. Functions to be developed: Build a Reinforcement Learning system that supervises and adjusts text generation through inputs and outputs. Develop automatic model selection algorithms
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processes with a focus on atmospheric applications. Contribute to the development and implementation of mathematical models and numerical algorithms. Analyze data from numerical simulations, climate models