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. Demonstrated experience in either of the following areas (a) data science, (b) theoretical nuclear reaction models and/or (c) deep learning-based machine learning and applications of artificial intelligence
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for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models to real-world data (RWD). Create innovative tools and solutions to extract deeper
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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, land-use change, and environmental dynamics. • Design and implement spatial analytics and geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and
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the project: Develop, train, and optimise deep learning models for wildlife species identification, classification, and segmentation using real-world datasets. Design and implement software modules to integrate
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, and machine learning models for functional genomics research in mycobacteria. Responsibilities Responsibilities include: Develop and maintain Django-based web applications and databases for sharing
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implement machine learning models dedicated to the prediction, interpretation, and quantitative analysis of Raman vibrational spectra, establishing explicit links between structure, local chemical environment
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associate in the broad areas of high performance computing and machine learning. HighZ is focused on developing scalable high order methods, enhanced with surrogate models for subscale physics, for modeling
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Engineering - Research and Development in Lisbon Scholarship Theme: Spatiotemporal Models for Sustainable Mobility and Urban Health in Medium-Sized Cities Duration: 3 months Maximum Duration Including Renewals