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Field
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Reference Number BAP-2026-500 Is the Job related to staff position within a Research Infrastructure? No Offer Description Modern embedded AI systems rely on Deep Neural Networks (DNNs) running on resource
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new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as
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11.11.2024, Academic staff In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In the project...
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(neural networks, model training and evaluation). Graph neural networks (GNN) or other current architectures (e.g. transformers). Causal inference or computer networks. Interpretability of AI (mechanistic
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new theoretical approaches for understanding stability, generalization, and feature learning in large-scale neural networks. Further details and application instructions are available at: https
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Develop soft, 3D-printed hydrogel bioelectronics for next-generation neural interfaces. Job description A 4-year PhD candidate position is available in the research group of Achilleas Savva in
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to brain networks and psychosocial systems”, PN-IV-P6-6.1-CoEx-2024-0139. Where to apply E-mail [email protected] Requirements Research FieldAllEducation LevelMaster Degree or equivalent Skills
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emotions make individuals susceptible to the experience of pain. By identifying and applying a translational model of emotional flexibility, the neural networks that underly comorbidities of fear and anxiety
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(Kirchhoff's laws) as soft or hard constraints, operational bounds (voltage limits, capacity, phase balance), and network topology through graph neural network architectures. You will build validated benchmark
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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's