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PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering
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Microelectronics teams, the PhD student will be supervised and helped. He/She will access, after training, the IEMN technological platforms. He/She will be provided the tools and computer accesses necessary
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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. Strong coding skills for programming neural networks, machine learning and machine learning software frameworks (e.g. PyTorch or Jax) is a must. The ability for creative and analytical thinking across
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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or Nextflow A willingness to learn and apply machine learning approaches Offer A doctoral scholarship for a period of 1 year to start, with the possibility of renewal for a further three-year period after
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within