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attitude, ability to work independently as well as in a team. Familiarity with green building technology, HVAC system study and optimization, sustainable building design, building energy modelling, CFD
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key master data domains (e.g. Person, Organisation, Vendor). The role focuses on identity resolution, survivorship modelling, API-first publishing, and event-driven data architecture — ensuring high
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models that support operational analytics, strategic reporting, automation, and emerging AI-driven insights. This role is critical to enabling data-informed decisions across academic, administrative, and
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of modelling and decision-support frameworks relevant to engineering and infrastructure systems. You should possess a good honours degree and a PhD (or equivalent professional experience) in Mechanical
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 24 days ago
the 21st century whether the focus is cancer, energy, economics or literature Connections working at Massachusetts Institute of Technology (MIT) More Jobs from This Employer https://main.hercjobs.org/jobs
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 8 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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companies' transitions towards a sustainable society. In research and education, we work in a broad spectrum. From basic mechanical engineering via modelling and simulation towards innovative product-service
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AI and related areas such as large language models (LLMs), prompt engineering, and machine learning. You are proactive about staying current in a rapidly evolving field. Rather than waiting for trends
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/10.1007/s11142-024-09822-y . He, L.- Y., Wang, L. (2025). Can artificial intelligence curb greenwashing? Firm-level evidence based on large language model. Energy Economics, 152, 108954. https://doi.org
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for converged Wireless-opTical cOnfiguratioNs”. The research will cover three key pillars: Artificial-Intelligence (AI)-driven models in the access domain, focusing on CF technology to efficiently acquire Channel