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Field
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This project offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute
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, motivation to learn new skills as well as excellent written and oral skills is essential.Example publications from the Lab:•Detection of host cell microprotein impurities in antibody drug products. 2024 Nature
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University
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calculations of well-characterized 2D materials, simulations of electron microscopy images, and machine learning methods to reconstruct the 3D atomic positions of materials from a 2D microscopy image. The
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, in addition to interfacing with the established Human-Computer Interaction (HCI) FIT lab. The candidate will be working alongside other researchers on the FLUIDITY project on human-robot interaction
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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that by combining electrospray deposition (ESD) with scanning tunnelling microscopy (STM) it is possible to deposit intact conjugated polymers in ultrahigh vacuum (UHV) and to acquire unprecedented sub