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patients, shoppers, and/or healthcare professionals Leveraging food retail, online delivery systems, and consumer-facing technology and information to advance Food is Medicine, including using artificial
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Sciences are Turing fellows. The Erlangen programme offers excellent opportunities for collaboration with a large team of scientists interested in the foundational issues of Artificial Intelligence and Deep
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Communications Research Centre, project EPROCESS EXTENSIONS financed by the Polytechnic of Leiria, in the following terms: . SCIENTIFIC AREA: Enterprise Architectures and Artificial Intelligence. . RECIPIENTS
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within the role to pursue an independent research project in the general remit of gene expression and the lab. Candidates with interest or experience in machine learning, artificial intelligence and
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model), Soil and Water Assessment Tool (SWAT model), and/or Noah Land Surface Model with Multi-Parameterization Options (Noah-MP model). Experience in either developing or applying Artificial Intelligence
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the field of Organisational Behaviour. Specifically, the focus will be on human-artificial intelligence (AI) collaboration and creativity as part of an ARC Discovery Grant. You will have the opportunity
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Tool (SWAT model), and/or Noah Land Surface Model with Multi-Parameterization Options (Noah-MP model). Experience in either developing or applying Artificial Intelligence and Machine Learning tools and
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environment and field experiments to investigate how beneficial microbiota enhance crop resilience to disease and climate stress. Apply advanced tools such as metagenomics, metabolomics, artificial intelligence
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
opportunity for a Level B Research Fellow to join a world-renowned team of researchers in the field of Organisational Behaviour. Specifically, the focus will be on human-artificial intelligence (AI
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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive