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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware
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systems Experience in deep learning, computer vision, or multimodal data integration Exposure to federated learning, privacy preserving analytics, or distributed systems Knowledge of clinical data models
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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for Languages) essential Strong programming skills in scientific computing languages (e.g. Python, C++) Solid knowledge of microgrid concepts and distribution network operation Knowledge of electric vehicle
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Systems. The project is sponsored by UKRI with the aim to conduct modelling, analysis and optimisation of smart power distribution grids and integrated power and transportation networks. In collaboration
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- Quantum Reinforcement Learning, quantum computing, QKD - quantum key distribution, entanglement distribution System-level design and optimization AI & Intelligence: Agentic AI, Edge AI, information
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, modeling, or AI/ML approaches in agricultural or environmental research. -Proficiency in server administration, distributed computing, and cloud platforms (AWS, Azure, Google Cloud). -Knowledge of full-stack
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2027 - 01:44 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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The School of Computer Science and Electronic Engineering at the University of Essex hosts research in communications, networking, signal processing and optimisation. The post will be based within
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-environmental and geographical situatedness of work environments in the ancient Roman Empire contributed to the spatial spread of ancient cults. Using computational methods, the project examines how