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Economics, Computational Science, Geography, Environmental Studies, or Engineering & Policy Analysis; Knowledge of a programming language (Python, Julia, etc) and training in any of the simulation methods
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
climate-related challenges. Proficiency in at least one programming language used for scientific or analytical purposes, e.g., Python. Excellent communication skills in English, both written and verbal
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for scientific or analytical purposes, e.g., Python. Excellent communication skills in English, both written and verbal. For more information about English requirements, please see: https://www.tudelft.nl
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or another relevant subject. Good Python programming skills. Knowledge of data science. Experience with artificial intelligence and machine learning. A good command of spoken and written English, as you’ll be
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physics. Proven programming skills in (preferably) Fortran or Julia, or C/C++ and Python. Where applicable, a link to your open source repositories is recommended. Other valuable skills include: Experience
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open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you will contribute: in the application of the developed
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, scanning system, and signal detection within a multi-beam framework. For this purpose, you will use commercial simulation software tools such as EOD and GPT, while also developing custom Python-based
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) and programming (e.g. Python, Matlab), with strong programming skills. Has knowledge of the steelmaking industry or of other process industry (e.g. modelling, experimental tests, techno-economic
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analytical skills, a strong interest in numerical modeling, and good programming skills in Python is required. Eligibility criteria Fulfillment of eligibility criteria is dictated by the European Commission
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. Experience in data analysis using Python. The outcomes of this project will be disseminated to the scientific community and a general audience through presentations at (inter)national conferences and through