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Field
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programming background with expierence in using Python, matlab, and/or Java, etc. a good command of German and English, both for teaching and for the preparation of research proposals and publications process
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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performance are expected. Required qualifications: Proficiency in programming (primarily Python or MATLAB) Strong communication and collaboration skills, including the ability to work across research groups and
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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with molecular biology, scRNAseq/ATACseq, in vivo 2-photon live imaging, and mouse behavior Experience with coding is an asset (e.g., R, Python, MATLAB). Ability to work independently and as part of a
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system modeling is beneficial but not mandatory First programming skills, ideally in Python Independent and analytical way of working Reliable and conscientious working style Fluent written and spoken
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communications Data Analysis and Management Implement and open-source proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C
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Knowledge of electronics, programmable logic, and processing systems is an advantage Strong analytical and programming skills are required (Python, VHDL, Matlab, and C/C++). Prior proven experience in data
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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field of study Interest in energy technology and energy economics Experience in energy system modelling is an advantage Basic programming skills, ideally in Python Independent and analytical way