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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
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chemistry models, and physics-informed deep learning, validated through field campaigns. Key Responsibilities Conduct atmospheric chemistry simulations Develop deep learning models for emission predictions
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intelligence, climate and sustainability science, aiming to develop predictive, decision-oriented, and operational frameworks for climate-resilient and sustainable territories. Research Scope and Objectives
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impeller performance, analyze hydrodynamic characteristics, and identify key synthesis parameters influencing material quality. The resulting models will act as a predictive tool for process optimization and
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concepts and profitability. In-depth knowledge of environmental sustainability standards. Experience with data prediction and classification techniques. Computer Skills Good proficiency with optimization
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Abstract: This position focuses on the development of intelligent and autonomous drone systems, integrating AI, edge computing, and digital twin technologies for mission autonomy and predictive
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and predictive tools to support system optimization and deployment strategies. Prepare