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analysis, critical thinking, scientific writing Your supervisors will help you identify your training and development needs, and use dedicated time and funding within the ARIES DT programme to support your
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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, and edge computing, AASs are evolving into smart, interconnected solutions for addressing the dynamic challenges of modern cities. This project investigates how to coordinate these multifunctional
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, Asian and Minority Ethnic. The research programme will take place in the interdisciplinary environment of the Communication and Electromagnetics group (https://www.birmingham.ac.uk/research/centres
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training programme by the University of Liverpool. As well as gaining a formal HE teaching qualification, you’ll learn key pedagogical skills for the academic job market, primarily through shadowing mentored
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also be involved in a fixed number of teaching hours during your time with us. In year one, alongside your specific PhD research modules, you’ll complete a short teacher training programme by
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Honours degree or international equivalent in a subject relevant to the proposed PhD project (inc. computing, mathematics, engineering etc.). Enthusiasm for research, the ability to think and work
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: Comparative transcriptomics, orthology inference, positive selection detection, protein domain analysis, phylogenetic comparative methods Computational skills: UNIX/Linux, HPC computing, R, Python You will gain
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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Project Supervisor - Professor Rudy Lapeer The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans