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of any university. Candidates will usually have completed their PhD or equivalent qualification but must not have undertaken more than 2 years postdoctoral work or work outside of academia by 1 October
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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of the research of Associate ProfessorDr Thomas Wälchli, MD-PhD, FMH neurosurgery is to understand how the brain vasculature is regulated during brain development, in the adult healthy brain, and in various
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record, and leadership. A PhD in a health-related discipline is essential; a PhD in Psychology would be an advantage, and understanding of qualitative approaches will be useful. You will have excellent
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collaborative research environment that exemplifies IDAI's distinct approach to interdisciplinary data science and AI research. Person Specification PhD (or near completion) in Computer Science, Data Science, AI
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. You will be routed to this when you click on the 'Apply' button. PhD degree in a relevant subject, such as chemistry, materials science or engineering. If you are near submission or have recently
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diversity, acting as a role model and contributing to an inclusive culture Person Specification First degree and normally a higher degree (e.g., MSc, PhD or near to completion) in a relevant field such as
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), or for application process queries Ruikang Xue (ruikang.xue@ucl.ac.uk). About you The successful candidate will have a PhD qualification, extensive knowledge and expertise in additive manufacturing, surface and bulk
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relevant PhD qualification. The title of Research Fellow will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience