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Field
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robots have the task to inspect underground sewer and clean water pipe networks. The robots are equipped with different sensors and with data from them can perform intelligent sensing and navigation
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Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO 13485, IEC 62304, MDD, and MDR Experience working within a team
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This PhD is part of the new Research England-funded Future Biodetection Technologies Hub and offers an exciting opportunity to contribute the advancement of development of new sensor technologies
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for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
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(Biochemistry, Neuroscience) MSc degree (or equivalent) in Epidemiology, Biostatistics, Data Science or related discipline. Strong quantitative analysis skills and experience developing algorithms and/or
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with the regulatory environment around Deep Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO 13485, IEC 62304
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pivotal role in analysing large-scale genomic and clinical data, applying cutting-edge algorithms, and collaborating with renowned experts in the field. At PBCI, we believe in fostering a collaborative and
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, sensors (e.g., proximity, temperature), actuators (linear, rotary), PLC systems (ABB, Allen Bradley, Siemens), and real-time data analytics Performing numerical and process simulations to verify structural
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, such as the IEEE International Conference on Robotics and Automation (ICRA), ROSCon and others. This PhD offers extensive transferable skills, including expertise in robotics, navigation, sensors, and
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degree in Chemical Engineering, Material Engineering, Chemistry, Nanotechnology or a related discipline. A PhD (or near completion) in electroactive materials, nanomaterials, electrochemical sensor