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Field
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product visuals, we bring complex technologies to life, making them accessible, desirable, and easy to adopt. We don't just showcase technology, we champion it. Acting as the bridge between cutting-edge
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, satellite communication systems, or energy engineering for wireless networks. Experience securing research funding, managing research programs, and building academic partnerships. Experience with embedded
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in
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successful candidate will conduct Density Functional Theory (DFT) simulations and develop machine learning potentials to investigate zeolite-related systems, particularly under complex chemical environments
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with GenAI industry and open-source communities. Key Responsibilities: Conduct the research in AI/ML domains, especially in probabilistic ML and scalable sequence network architectures Produce academic
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Multimodal Models Generative AI, Agentic AI, Physical AI, and Embodied AI Trustworthy AI, including explainability, auditability, and privacy Edge AI and model optimisation Physics-informed neural networks
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basics of programming languages such as ROS and Python Excellent communication skills, written and verbal – able to communicate complex concepts clearly and accurately We regret to inform you that only
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, 3D PCA, or other dimensionality reduction methods for integrating complex, multimodal datasets. Experience working with limited sample volumes, and ability to design robust experimental protocols
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Embodied AI Trustworthy AI, including explainability, auditability, and privacy Edge AI and model optimisation Physics-informed neural networks (PINNs) and surrogate modelling Time-series modelling and
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bringing together the University of Plymouth, NHS partners across Plymouth and Somerset, and a wide network of collaborators, including King’s College London. The programme aims to transform how routinely