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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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Hospitality performance and revenue optimization Tourism analytics and predictive modeling Sustainable tourism and community engagement Technology, AI, and smart destinations Indianapolis provides a living
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the EU Research Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description QSAR Lab is an R&D company specializing in computer modeling
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visualization of high-dimensional omics data from the field of bioeconomics, and in the modeling, simulation, and engineering of biomolecular systems, including enzymes. Apply your data science skills to real
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to improve predictive models and inform design strategies. Work in Practical Settings — engage directly with NIHE to implement and test research methods in operational housing schemes. This work will equip
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of Robotics and Industrial Informatics (CSIC-UPC) offer a position to work on World Models for Human Behaviour Anticipation https://ramonllull-aira.eu/archivos/theme_field/world-models-for-human-behaviour
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materials databases to be integrated into the NIST-JARVIS (https://jarvis.nist.gov/ ) infrastructure. We work closely with experimental collaborators for validation and focus on releasing software, models
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 23 days ago
families that may differentiate thermotolerant Arctic algae from strict cryophiles. Particular focus may be made here on closely-related polar members of the model green algal species Chlamydomonas that have
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar
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factors such as prediction of plant growth, water pollution, and environmental biodiversity loss. The approach seeks to create robust, explainable models that reflect domain-specific insights, advancing