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, or a related field of study Knowledge of energy process engineering is an advantage Huge interest in energy technology and economics Experience in energy system modeling is beneficial First programming
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: You will strengthen the data science and machine learning
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Profile: Masters degree in physics, materials science, physical chemistry, electrical engineering and related disciplines Very good grades in the masters and bachelors degrees are mandatory Knowledge
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Your Job: As PhD student you achieve fascinating insight into catalyst interfaces with the following tasks: Synthesis of model catalyst interfaces Participation in neutron scattering experiments
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results in reputable scientific journals to share knowledge and contribute to the advancement of the field Your Profile: Completed Master`s degree in the field of economics, social sciences, data science or
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engineering, or related field Knowledge and competences in physical theory and modelling Experience and interest in computer programming Basic knowledge of electrochemistry and electrochemical energy
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, including JUPITER, Europe`s first exascale computer Prepare, process and publish datasets and benchmarks for self-supervised learning in science Engage in national and international ML/DL communities, most
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of an innovative shim insert necessitates a blend of robust engineering skills and advanced simulation methodologies spanning various physical domains. To meet this challenge, ZEA-1 and INM-4 will integrate
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thesis. Your Profile: Successfully completed Master`s degree in the field of materials science, engineering, physics or chemistry or a similar field Very good knowledge in the field of solid-state
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: Successfully completed Master`s degree in the field of materials science, engineering, physics or chemistry Very good knowledge in the field of solid-state chemistry and materials engineering Experience in