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Field
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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film characterization, x-ray spectroscopy or electrochemical characterization in desirable Fluent knowledge of written and spoken English High degree of motivation and reliability and analytical working
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and analytical working style Excellent ability to cooperate and work in a team Fluent knowledge of written and spoken English Our Offer: We work on highly relevant innovative topics and offer you the
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project position as Research Associate / PhD Student (m/f/x) within the MSCA Doctoral Network SLICE (due to funding, the salary is calculated according to MSCA regulation) starting October 1, 2026
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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of electrolysis Prior knowledge of electrochemistry desirable Willingness to learn additional electrochemical methods Good analytical and data processing skills with open source software, e.g. Python High degree
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computer systems. Write reports and research articles, as well as grant proposals, and regularly participate in international conferences to present your own work. Your Profile: Master with subsequent PhD
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and reality gap bridging for deformable object interaction (using environments such as MuJoCo, PyBullet, or NVIDIA Isaac Sim) Adaptive feedback control using learned and analytical models Physics
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excellence, and continuous learning in close cooperation with core facility heads, administration and researchers Your Qualifications: PhD or an equivalent degree in a relevant scientific discipline Several
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unit Analysis and interpretation of measurement data and preparation of scientific publications Requirements: PhD degree in discipline of the natural sciences, preferably chemistry Knowledge and