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be applied upon successful completion of the PhD. The candidate should have a background in quantitative methods or applied/social statistics. The candidate must show evidence of working independently
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-holder will have the responsibility for communicating complex information effectively to clinical scientists and non-statisticians. You will have an MSc or PhD in Statistics, and experience or an interest
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complex health and social care challenges, particularly in the management of long-term conditions. We combine AI and traditional epidemiology with qualitative methods to develop impactful, real-world
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physical or mental health conditions, neurodivergent students (such as those with autism and ADHD), and those without a formal diagnosis of disability. In this role you will be responsible for a team that
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) cell activation against blood cancer and is expected to identify novel therapeutic strategies to improve the outcome for patients. You will be part of a team of research technicians, PhD students
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including a large 6-axis motion simulator and a suite of acoustic chambers. You will have a PhD or equivalent experience in structural dynamics and vibration, and an impressive publication record in high
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methods (statistics, ML, AI) with applications to energy and built environment problems and programming languages e.g. Python, R, Matlab, C# etc applied at highlighted scales. About you We welcome
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and device characterisation is essential. A PhD in silicon photonics is desirable. A proven track-record in leadership and managing a team and demonstrated experience in establishing a technology
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About MINDS Centre for Doctoral Training The Machine Intelligence for Nano-Electronic Devices and Systems (MINDS), is a very successful £5M Centre for Doctoral Training (CDT) funding around 50 PhD
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systems, and ideally some exposure to macOS or Linux A calm, methodical approach to resolving problems, even when under pressure Strong communication skills and a clear, approachable manner when working