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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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Primary Supervisor -Prof Michal Mackiewicz Scientific background Marine litter is a key threat to the oceans health and the livelihoods. Hence, new scalable automated methods to collect and analyse
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for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance. Your RoleAs a PhD researcher, you will: Build and validate hybrid
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of transformer parameters (no-load losses, winding gradient, load losses). Building upon this existing body of work, the proposed research project aims to explore AI models and ML algorithms which are suitable
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Interplay between Algorithms and Combinatorics
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their thesis research. The candidate will work closely with Prof. Olivares-Mendez and Dr. Carol Martinez, the members of the Space Robotics (SpaceR) research group (www.spacer.lu ) and Redwire Space Luxembourg
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deployment and post-training of foundation/large models”. He/She will be required to: (a) model quantum computing platforms; (b) design quantum networks and compilation algorithms; (c) evaluate
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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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position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient 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