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per year for 3.5 years. Lead Supervisor’s full name & email address Dr Massimiliano Fasi: m.fasi@leeds.ac.uk Project summary The growing importance of artificial intelligence is fostering a paradigm
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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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of analysis and visualization software Very good written and spoken English skills are required Furthermore, experience in dealing with the ICON model and the scientific utilization of ICON data is an advantage
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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purification is desirable but not necessary. Candidates with physics and physical chemistry are encouraged to apply. Knowledge of coding and image analysis is desirable but not necessary. As well as supporting
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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(spoken and written). Preferred qualifications Prior experience with 3D cell culture, organoids, CRISPR-Cas9, or imaging-based phenotyping. Familiarity with transcriptomics or basic computational biology (R
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Scholarship code: SRS-25030 These prestigious La Trobe University scholarships (2), in partnership with the Australian Office of National Intelligence, will be awarded to outstanding applicants
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assaulting them. Second, technology has contributed to the creation of new forms of sexual harm, such as image-based abuse and deepfake technology. The implications of these developments are twofold. First
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complex systems and their role in the evolution of life. One of the key features of life is the presence of its essential molecules, such as amino acids, proteins, sugars and DNA, as a single mirror image