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serine recombinases (LSRs) and their directionality factors (RDFs) as a model. You will design, implement and benchmark machine learning pipelines for sequence-structure analysis and protein function
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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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of Aberdeen to work on a project “Predicting Response in Triple Negative Breast Cancer Using Machine Learning”. We seek to appoint a creative and motivated individual to use machine learning (ML) to identify
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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mathematics, statistics, or machine learning, or a closely related discipline • OR near to completion of a PhD • Expert knowledge of Bayesian computation and deep learning methods • Excellent
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and execute methods for characterizing and linking the texture and
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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or machine learning. Excellent programming skills in Python and deep learning frameworks. A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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transformations. Combining automated reaction discovery simulations, microkinetic modelling, machine learning, and global optimization, this project will develop a new and exciting route to addressing one