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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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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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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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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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information that is processed through a machine learning element. The role will also require regular contributions to a variety of academic tasks, including positively interacting and communicating with
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The Division of Informatics, Imaging and Data Sciences in the School of Health Sciences wishes to recruit an enthusiastic and innovative individual to a teaching focussed role of Lecturer in Digital
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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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opportunity to work at the intersection of multimodal AI, cancer biology and digital pathology. The successful applicant will have a PhD or MSc with a significant machine learning element and/or experience with
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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