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Field
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Develop new ML algorithms for cell-biology applications where needed Plan data acquisitions with experimentalists who conduct them, analyse and interpret results and supervise delivery of outputs (e.g
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the use of AI to support the triage of adult brain MRI scans within routine clinical practice. The intervention under investigation is a UKCA Class I–certified deep learning algorithm designed to assist
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, anomaly detection, and fault prediction algorithms for rotating electrical equipment. Analyze electrical, thermal, and vibration signatures for early detection of bearing faults, winding faults, imbalance
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. Implementing a novel algorithm to embedding and vectorising the data. Design the optimum combination of AI Language Modules to meet the needs of Company’s customer base. Designing and engineering the prompt
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. The success of neural networks as a platform for developing AI is partially explained by the fact that backpropagation, the primary algorithm used to train them, runs efficiently on conventional CMOS hardware
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, layout and application of deep submicron technologies Embedded systems design and algorithms for embedded software systems. Design of micro-electro-mechanical systems including sensors, amplifiers, mixed
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well as competence in mathematics including probability, statistics and algorithms. Keen interest to support research and academic project work, with demonstrated ability in developing software solutions to technical
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well as competence in mathematics including probability, statistics and algorithms. Demonstrate proficiency to keep abreast of developments in the field and pursue professional certification programs. Possession
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
, international collaboration, and data crawling Develop algorithms to process and clean large and diverse ionospheric datasets. Share research findings through publications, research seminars, etc. Guide and
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. This longitudinal project investigates the implementation of AI-empowered chronic disease management systems in hospitals. It examines human-AI collaboration and the "boundaries of work" between humans and algorithms