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on such jets — although their detailed properties remain unexplored. In this project, we will develop new computational methods to compute and characterize these novel wave solutions, with particular emphasis
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critical mass on distributed radar, which is currently supported by prestigious and large initiatives including QuSIT and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on distributed
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), machine learning (ML), deep learning (DL) and Data science methods for medical image analysis, to autonomously grade the fundus images from large datasets. This will be supported by Professor Neil Vaughan
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chance to learn about computational modelling of development. We encourage applications from highly motivated candidates with a strong academic background in psychology, cognitive science, speech and
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Are you fascinated by working at the intersection of physics and synthetic biology? This PhD project offers a unique opportunity to develop autonomous microswimmers, which are bioinspired structures
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within the Vienna Doctoral School in Chemistry (DoSChem) – Austria’s largest doctoral training program in chemistry. DoSChem brings together more than 200 doctoral students and over 50 PIs, fostering
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Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How to apply Please read and complete this document as your Personal statement, and upload
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undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and spoken communication skills The following skills are desirable but not essential: Background in
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Engineering or Computer Science. We would also like to see experience in: Machine Learning, Optimisation, Python, finite elements How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and
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Main description: Native mass spectrometry is an expanding structural biology tool to elucidate the function of protein complexes. Excitingly, the demand for this technology is increasing. However