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) of the following: energy systems analysis with mathematical optimization (emphasis on adequate modelling, problem formulation), electricity markets, renewable gases (e.g. hydrogen). Provable programming skills
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discipline. Good written and oral communication skills in English are needed. The individual should have a self-dependent mindset, good leadership qualities, and a strong foundation of practical relevant
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to run a world-class research and teaching program that emphasizes industrial translation of Artificial Intelligence methods within a Design and Manufacturing context. This position is envisaged to be part
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the Community Earth System Model (CESM) Strong programming skills are required. Good knowledge of English (spoken and written) is essential. Employment will be according to standard regulations at ETH (funding
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detection, quantification, or catalogue analysis. Programming skills in Python; experience in scientific software development and C++ would be regarded positively. Familiarity with seismic data processing and
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, supported by an excellent command of German and English, and preferably have working knowledge of French. Ideally, you are willing to hold office for at least two terms (i.e. eight years), and could assume
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integral partof your work, you will publish your results in peer-reviewed journals and present them at international conferences. Profile You meet the requirements for a doctoral program at ETH Zurich and
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, mechanical, or industrial engineering. You are driven by an interest in developing novel theory and methods for solving real-world problems. Programming, modelling, and data analysis skills in python and
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processing, or condition monitoring Programming proficiency in Python, MATLAB, or comparable environments Strong interest in applying AI to real-world manufacturing problems Required people skills Self
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-hand data collection, such as questionnaire design. Very good knowledge of written and spoken English (C1 or higher). (Some) knowledge of programming and data analysis and a willingness to familiarize