101 machine-learning-and-image-processing-"RMIT-University" Fellowship positions at Nature Careers
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International travel may be required for this role. Background This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop
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foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing can be
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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computational biology and immunology are also welcome. Our laboratory focus ranges from the study of basic biological processes to very translational bench-to-clinical research with implementation of laboratory
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biology, ideally having studied lubrication biology in the joint Experience in molecular biology, computational immunology, bioinformatics and multi-dimensional imaging including light-sheet and 3D tissue
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website. Online Info Sessions for Prospective Candidates Join our upcoming online info session to learn more about the fellowship, eligibility, and application process. Details and registration
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neurons using patch-clamp recording, single-cell electroporation, Patch-seq, and advanced imaging approaches. Characterizing synaptic plasticity during navigation and learning using two-photon calcium
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changes and established markers for Alzheimer's disease. The project may also include machine learning methods to estimate individuals' biological age. The project is based on existing data from a prominent
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researchers and innovators, making discoveries and generating solutions that make the world healthier, safer, stronger and more just. Learn more . Working for the Department of Pharmacology The University