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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
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/10.1101/2022.11.14.516440 [3] Triage-driven diagnosis for early detection of esophageal cancer using deep learning http://doi.org/10.1101/2020.07.16.20154732 Preferred skills/knowledge We are seeking a
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of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable
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workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing
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. Cranfield University is a world-leading postgraduate institution renowned for its applied research and deep industry connections, particularly in aerospace, defence, and security. Its Centre for Electronic
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this project, you will combine a deep knowledge of physical chemistry with robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning
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of topics is covered, from large-scale data management to data mining and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics
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deep learning, preferably including some exposure to graph neural networks or geometric deep learning. Proven experience with implementing machine learning methods in Python and Pytorch. Familiarity with
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experimental data (from ex-situ and in-situ measurement). Therefore, she/he will develop a way to optimize/guide the experiments trough artificial intelligence approach (machine/deep learning) that he will
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). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background