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multifractal analysis, urban and energy planning, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net
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talented candidate with a Master’s degree in civil engineering, mechanical engineering, or a related discipline Solid background in mechanics of materials and finite element analysis Sound knowledge
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Science, Computer Science, or a related disciplines. The candidates should have: A solid theoretical background in their field Strong programming skills and experience with numerical methods. Proven
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, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net Land Take. The consortium comprises four
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in Mechanical or Aerospace Engineering, Physics, Computational Science, or a related discipline. The candidates should have: Solid programming skills (Python, MATLAB, or C++). Knowledge of the OpenCV
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the University of Zurich. Your profile Master's degree in Earth Sciences, Geography, Physics, Environmental Sciences, Meteorology, or a related field. Passion for atmospheric remote sensing, chemical
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sensing systems Design and validate machine learning models for predictive monitoring of physiological states Analyse large experimental datasets and quantify sensor performance (accuracy, robustness
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Stage Researcher (R1) Application Deadline 14 Apr 2026 - 21:59 (UTC) Country Switzerland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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sciences » Other Researcher Profile First Stage Researcher (R1) Country Switzerland Application Deadline 29 Mar 2026 - 21:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through
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First Stage Researcher (R1) Country Switzerland Application Deadline 23 Mar 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme