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Field
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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training programme in respect of industry-specific skills, and access to hotfire facilities at Westcott, Machrihanish, and elsewhere. You can learn more about the programme at r2t2.org.uk. Kick stages are a
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc