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Description The „Karlsruhe School of Elementary Particle and Astroparticle Physics: Science and Technology (KSETA)” is the Doctoral School of the KIT Center Elementary Particle and Astroparticle
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language
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Dresden explores and develops novel quantum materials with tailored properties. Around 300 researchers from over 30 countries work at the interface of physics, chemistry, and materials science to lay
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developed into its vibrant center. The newly DFG-funded Research Training Group “Biomolecular Condensates: From Physics to Biological Functions” (RTG 3120) at TUD Dresden University of Technology offers
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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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apply a data-driven approach to cross-scale materials discovery and design, in particular, goal-oriented, inverse design procedures based on process-structure-property linkages are of interest
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to vpajob at tu-dresden.de or to: TU Dresden, Chair of Traffic Process Automation
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well as share research knowledge via teaching. Qualifications The candidate will hold a Master’s in Chemical, Process, Environmental Engineering, or equivalent, and is a naturally curious person who is eager
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institutions from academia and industry: https://euraxess.ec.europa.eu/jobs/401249 . Your mission The aim of the project is the development of a physical model of the initial solidification of steel during
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of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD