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We are recruiting a lead post-doctoral researcher with a background in nutrition for an ESRC funded project on ultra-processed food, nutrition and eating behaviour. The researcher will join the
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and mathematical approaches to signal analysis, information theory, computational biology and image processing. The term of appointment is one year with the possibility of renewal pending satisfactory
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sensing, signalling and memory, critically influences the disease onset and progression1. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is
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The overall goal of our research is to describe a class of organic materials able to transport ionic and electronic charge which provide an ideal interface between human-built devices (where signals
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processes that underly normal and abnormal cardiovascular and metabolic function and drive the translation of this strong basic science into advances in clinical practice. Our research focuses on four main
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to investigate the chemical diversity, biochemical interactions, and biological roles of plant and fungal natural products, with an emphasis on specialized metabolites, signalling molecules and relevant molecular
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PhD (or be near completion) in a field such as AI, computer science, signal processing, biomedical engineering, have a strong record of publication in engineering or computer science literature, and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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sensing, signalling and memory, critically influences the disease onset and progression1. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is
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before September 10, 2025, and include: A full Curriculum Vitae. Your CV should demonstrate the scope of your work and education and indicate a good fit with the stated requirements for the position. A