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of digitalised services, particularly in the areas of housing, health and energy. We will draw on knowledge, methods and skills from social policy, cyber security and privacy, data mining and machine learning
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addition to the above, you will have experience in structural design as well as computer programming experience. With excellent communication skills, you will also be a good team player, enjoy presenting, and have the
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Management (UAM). About You You will be educated to doctoral level (or close to completion) in Aerospace Engineering, Control Engineering, Electronic Engineering, Machine Learning, or related fields. You will
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developing behaviour monitoring or anomaly detection algorithms based on machine learning. You will have substantial understanding of estimation theories, systems and control, optimisation and optimal control
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in Networked Autonomy with experience in designing, training, and validation of autonomous systems that contain elements of wireless communications, navigation/control, and machine learning. About the
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/ mechanical / electrical / computer engineering subject. Knowledge of sensors modelling and data training is essential for the post. Expertise in machine learning algorithms deployment for the optimization
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reputation for leading in the field of digital systems: sensor data and signal processing for position, navigation and timing, machine learning - has been established through active research in this field
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coordinating research activities and will need excellent interpersonal skills. About You For Research Assistant you will hold a BEng and/or MSc in an aerospace / mechanical / electrical / computer engineering
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per annum Cranfield University School of Aerospace Transport and Manufacturing and the IVHM Centre welcomes applications from engineers - scientists with expertise in computer programming and/or