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applications in different project contexts. This may include data analysis, modelling, literature reviews, and interaction with relevant stakeholders. The results are expected to contribute increased knowledge
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AI infrastructure. The Opportunity This is an unprecedented opportunity for an outstanding data science and AI PhD candidate interested in brain data analysis and AI, supervised by Dr Mahsa Salehi
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solution for the future of maritime decarbonisation. Your work tasks The research assistant will be involved in high-fidelity numerical modelling and a comprehensive analysis campaign of flexible power
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PhD Position: Engineering Trustworthy Energy Data Spaces for Heat Transition Planning How can heterogeneous energy data be shared securely and efficiently to accelerate the heat transition
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solutions to PDEs . Your work will involve utilizing GPU code generators for matrix multiplication kernels and ensuring the software is usable in Python for downstream data analysis [2]. Collaboration is
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tackle the socio-techno-economical complexity of the built environment. Your vision is to close the “performance gap” by integrating Advanced HVAC System Design & Control, Cyber-Physical Modeling, and
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Requirements Research FieldEngineeringEducation LevelMaster Degree or equivalent LanguagesENGLISHLevelExcellent Research FieldEngineering Additional Information Website for additional job details https
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, but its human burden is badly understood. This PhD addresses this gap, integrating multiple high‑value datasets describing metagenomic and metatranscriptomic sequencing information, clinical and
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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dynamical systems methods and data-driven analysis is a plus We offer Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes