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. - Knowledge of programming languages for instrumentation (LabView, Python) Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5589-BAPALL-001/Default.aspx Work Location(s) Number of offers
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
: 265566 Vacancy ID: PDS003971 Position Summary/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to pursuing
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., MATLAB, Python) Understanding of thermodynamics and gas transport processes Ability to develop, implement, and test numerical algorithms Ability to work independently and collaboratively in a research team
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ETHOS.HiSim, a python package to simulate households and building systems. Identification of techno-economic data for buildings, retrofitting options, heating and cooling systems, and the building stock
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Assistant to support an AI-enabled battery
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statistical and econometric analysis, and produces tables and figures using statistical programming languages (R, Stata, or Python) Writes memos summarizing methods and results, and contributes to academic
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: “The Biomedical Data Translator.” https://ncats.nih.gov/research/research-activities/translator These programmers will develop the following components to be incorporated into the ARAX (https://github.com/RTXteam
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Mathematics, or similar) Experience in energy modeling, optimization, or advanced algorithms Programming skills (Python, Matlab, or similar) Spanish and English required What We Offer High-impact national
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Vector, Vue.js 3, Node.js, Python, and JSON; Natural Language Processing (NLP) applied to collections; implementation of data pipelines using AI models, embeddings (RAG), and OCR; demonstrated knowledge in