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PhD Studentship: Multi-robot Cyber-physical Systems for Solar Farm Health Monitoring and Maintenance
of operation and power requirements. Applicants should have a First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics
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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is
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% average), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success
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science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants . Funding Tuition fees + stipend are available
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*Home fee status applicants from a Law background are invited to apply* The Centre for Doctoral Training in Safe AI Systems (SAINTS CDT) is the UK’s first multidisciplinary PhD programme focused
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machine learning (applied to spatiotemporal data). International and UK applicants are both eligible to apply. Sponsor: This scholarship is funded by the UK Engineering and Physical Sciences Research
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-class honours degree, or suitable postgraduate degree in computer science, human factors, psychology, social science or a health or social care related subject. Funding notes: This PhD scholarship is
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to the fields of synthetic biology, bio-derived materials, and bioinspired design. The outcomes of this research will provide a foundation for understanding and replicating natural mineralisation processes