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The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
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achieved through a variety of optimization, machine learning or AI-based heuristics. Optimization of revenue stacking models for hydrogen assets that have to supply a number of market-based services
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carbonate stratigraphy, structural geology fundamentals, and manipulation of seismic data. Formalized training on the use of machine learning and AI workflows that can be transferred to geoscience
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, enabling the monitoring of critical process parameters (CPPs) and critical quality attributes (CQAs). Nestling wishes to collect the data and apply machine learning techniques to identify process efficiency
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Types Using Machine Learning Based on Citizen Science Audio Recordings and Satellite Imagery” (Bio-O-Ton-2). Our overarching goal is to develop and test novel machine-learning approaches for combining
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at developing novel materials with the potential to drive advancements in multiple industries. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality
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machine learning model to optimise sensor configurations (for multiple unit sensors) for a given application. The project will bring together Soft Matter, Biomedical Engineering and Data Science to generate
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of structural and dynamic properties of molecular switches and machines Development and application of evolutionary algorithms, neural networks and machine learning for modeling, evaluation and visualization
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
the complexity and capabilities of Machine Learning (ML) models have made Artificial Intelligence (AI) able to tackle challenges ranging from vision and graphics to natural language, and even creative tasks
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/technical challenges Project FITNESS will build upon and extend state-of-the-art methods [1], [2] recently developed within the team, showing to outperform existing, machine-learning based approaches in