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ranging from simulated environments (e.g., Web browsers, Videogames, etc.) to Robotics tasks. Candidate’s profile A good Bachelors degree (2.1 or above or international equivalent) and/or Masters degree in
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, will be trained on simulation data to create dynamic, adaptive control systems that optimise operation in real-time across multiple variables. This research will deliver a validated roadmap to 60
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of Robot Behaviours in Simulation: Develop methods to automatically generate diverse test scenarios in a virtual environment to efficiently find faults in robotic skills. This involves using intelligent
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models. The project’s key objectives are to: 1) Identify critical indicators relating to ecosystem health and resilience; 2) Incorporate indicators into DBN models to simulate how ecosystems respond
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at the genomic level by examining the variation in copy numbers of ecologically relevant genes, differential selective pressures on key genes, and changes in gene expression regulation related to nitrogen
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similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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Investigator: 1. Contribute as part of an interdisciplinary team to the creation, quality control, and usage of a novel full-scale digital twin dataset for the UK and related simulation infrastructure. 2
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, and simulations across physics, chemistry, and engineering. Applicants should have, or be expected to gain, a high (1st or 2:1) honours degree in Physics or Chemistry. Fixed-term: The funds
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, please provide a cover letter explaining why you are a suitable candidate, including what you consider are the main challenges for the health and care workforce. Please also include a copy of your CV