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performance, yet their atomic-scale origin and role in reactivity remain poorly understood. The project addresses this open problem by integrating high-throughput Density Functional Theory, machine-learning
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Grant/funding reference: PID2023-149956OB-I00 Job title: Safe and efficient ports: comprehensive operational risk management through monitoring, advanced techniques and machine learning. PORT-AHEAD+AI
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, they will take an active role in designing and commissioning a pioneering Self‑Driving Lab, a next‑generation autonomous research platform that will integrate Machine Learning and Bayesian optimization
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Predoctoral Researcher (PhD Candidate) in Computational Simulation and AI for Therapeutic Ultrasound
research. • Availability to work on-site in Madrid (Spain). • Ability to enrol in an official PhD programme in Spain. • Interest in numerical simulation, machine learning and clinical applications of focused
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to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and electronic
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. Pablo Carbonell, creates innovative solutions for automated biofoundries, fostering sustainable industrial biotechnology across the bioeconomy sectors. The lab combines synthetic biology, machine learning
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biofoundries, fostering sustainable industrial biotechnology across the bioeconomy sectors. The lab combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce
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Publications relevant to the position: J. M. Montes-Lopez, P. Serrano, M. Gramaglia, A. Banchs, “DiWi: A Transformer-Based Digital Twin for Wireless Mobility”, Elsevier Computer Networks M. Milani, V. Vomhoff, D
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computing and decentralized intelligence where a swarm of nodes learns graph dependencies by effectively integrating the structure of distributed systems into neural network architecture. This approach
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience