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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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of a Class B driver’s license are also required. Please find more information about the position, the contact person and the link for applying here: https://jobs.rptu.de/jobposting
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PhD Position – High-Temperature Electrolysis – from stack design to operational optimizationFull PhD
digitalized society, a climate-friendly energy system, and a sustainable economy. We focus on the natural, life, and engineering sciences in the fields of information, energy, and bioeconomy. We combine
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StreetLansstraße 7-9Zipcode14195CityBerlin Contact details Tel:+49-30-838-52868 E-Mail: office at gsnas.fu-berlin.de Web: https://www.jfki.fu-berlin.de/en/graduateschool/index.html Legal notice: The information
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compensation beyond the base salary may be possible. All information about the TVöD Bund collective agreement can be found on the BMI website (pay scale table on page 66 of the PDF download): https://go.fzj.de
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of Photogrammetry and Remote Sensing and together with other chairs being part of the RTG. Requirements: good or very good university degree in electrical engineering, computer science, computer engineering or
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interdisciplinary research environment, where you'll work alongside experts from fields such as engineering, data science, urban studies, and aerospace. Skill Development: Our extensive qualification concept goes
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Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning
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, physics, or data science. They should have strong analytical skills in the context of machine learning and/or numerical mathematics, as well as an excellent command of a programming language, preferably
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2027). Cross-Disciplinary Collaboration: Immerse yourself in a highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as engineering, data