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(or equivalent) or a Masters degree in a social science or related discipline. Have or be about to obtain a PhD in a relevant subject. Experience: Relevant research experience working on a project that relates to
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or machine learning to complex data. The successful candidate will have (or be nearing completion of) a PhD in a relevant field such as polymer science, materials engineering, or mechanical engineering
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by Professor Ara Darzi, while working towards a PhD degree . The research project will entail project design, experimental work in addition to data analysis and reporting the results in peer-reviewed
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research associates and PhD students. You will also engage directly with numerous external stakeholders (industry and academia), which will form part of your research network and give you opportunities
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software development is desirable. A PhD, a strong publication record, and excellent technical communication, reporting, and presentation skills are required. Due to the nature of this role, you will be
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with a wider interdisciplinary research team Participate in wider networks, including the Adult Social Care Cluster and DEMCOMM programme events Main Duties The responsibilities may include some but not
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: robotics, smart technologies, software engineering, security and data analytics. You will be contractually enrolled into the Teachers’ Pension Scheme (TPS) – one of the largest and most generous defined
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postgraduate degree, ideally a PhD, in statistics, machine learning, or a related field. Experience of developing new statistical methods and a strong working knowledge of a statistical software package, such as
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technical planning and delivery. Lead the development of hardware-software integration workflows for monitoring, diagnostics, and control of battery systems. Produce high-impact research outputs (journal
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and FDS is preferred. Candidate preferably should be familiar and have sufficient experience in using ANSYS FLUENT and FDS, Meshing tool and post-processing software. Able to work independently with