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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description HIV remains one of the most persistent and challenging infections
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Theoretical models for gravitational wave signals emitted by coalescing compact binaries are the cornerstone of modern gravitational wave astrophysics. Among the most pressing challenges
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Understanding tyre–road surface contact is critical to achieving desired vehicle performance. Friction is a complex property, unique to each system, and challenging to measure and model. To explore
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low-cost PCM composites the RecyWax+ project combines multi-physics modelling approaches and physical experimentation of the thermal properties of the PCM composite. Throughout, theory is validated by
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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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Vacancies PhD Position on Neural Engineering/Computational Neuroscience/Biomedical Engineering Key takeaways We are seeking a highly motivated PhD candidate to join a multidisciplinary team working
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nano-computed tomography, and scanning electron microscopy design and implement deep learning models to enhance resolution of large field-of-view imaging techniques integrate imaging data across
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. Qualifications: • Completed academic university degree (Master level) in mathematics, computer sciences, physics or a related discipline • Knowledge of programming, machine learning methods, mechanistic modelling
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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validation of the numerical model. Candidates should be holding a MSc degree in Engineering (or equivalent), with demonstrated experience in computational fluid dynamics (CFD), preferably in hydraulic