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behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning, experimental psychology, audiology, cognitive
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We are looking for an ambitious Research Associate who is passionate about generative AI, synthetic data, and in-silico trials to join our multidisciplinary team. You will work with colleagues who
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leverage clinical and experimental datasets, apply physics-based simulations, and harness the power of scientific machine learning, including data assimilation and uncertainty quantification. Additionally
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primary cultured hepatocytes. These in vitro data will be subsequently used to inform mechanistic physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD) models, enabling bottom-up predictions
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approach is one of the distinctive features of data science at Manchester. You should have a PhD (or equivalent) in statistics or a similar field, and be developing your publication record. You should have
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to demonstrate the following: is in possession or close to submitting a PhD degree in a relevant discipline (e.g. physics, materials science, computer science, electrical & electronic engineering); has hands
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required Work closely with senior technology leads to ensure the timely and appropriate flow of data and protocols across the platforms to support the scientific vision. What you will get in return
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The School of Engineering has an opportunity for a Research Associate, working with Prof Cise Unluer, to make a leading contribution to ongoing projects involving the integration of industrial
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Engineering and Spintronic Technologies (NEST) group. The NEST group is a vibrant community of interdisciplinary researchers working on a variety of topics including spintronics, magnetic data storage, nano
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, or knowledge representation. You will be working closely with a team of PhD and Postdoctoral researchers from The University of Manchester, who are developing the underlying technology. You will also be working