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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 14 hours ago
will engage in multiscale modeling and machine learning to develop reliable, efficient framework for predicting long-term creep and fatigue behaviors of heat-resistant structural alloys considering
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associates in Artificial Intelligence (AI) in Biomolecular Modeling. The postdoctoral associate will focus on developing and applying AI methodologies to drive advances in drug discovery and biomolecular
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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to developing, designing and conducting research projects under general direction of the PI but in self-driven fashion; developing appropriate research methods; creative use of animal models; data analyses and
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, distributed control, formation control, perception, and decision-making in complex environments. Design and implement data-driven approaches, including machine learning, reinforcement learning, surrogate models
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on developing multi-scale mechanical models to predict how printed inks behave under mechanical and environmental stress. Your role: Build multi-scale models and extend the Eindhoven Glass Polymer Model for latex
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to use data and modelling to make historic buildings energy efficient – without compromising their cultural value? Join the research project DASHER at KTH. DASHER (Data-driven Structured Historic Energy
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David Levinson , the successful candidate will contribute to the development of hybrid quantum-classical modelling approaches that support improved analysis, simulation, optimisation, and decision making
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. For more information about the RNA Technologies Flagship, visit: https://rna.iit.it/ The project aims to develop a new generation of artificial intelligence models to systematically investigate the role
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methods for the modelling and causal analysis of mass transit systems. The research will focus in particular on the development and application of data science methods to address key challenges in capacity