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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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or above. have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding. How to apply
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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML
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rapid and significant shifts in power consumption, next-generation high-performance computing (HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs
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implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning