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of the influence of the electrolyte on the overall cell performance under varying conditions Documenting and visualizing the achieved results in presentations Your Profile: You are enrolled in a master`s programme
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English or German, according to the candidate’s preference. Full-time / part-time full-time Mode of study 50 / 50 online and on-site Programme duration 6 semesters Beginning Winter semester Application
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choose their own courses to some extent. Application deadline https://www.iri-thesys.org/education/graduate_program/membership Tuition fees per semester in EUR None Combined Master's degree / PhD programme
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specifically for doctoral students (HITEC): https://www.hitec-graduate-school.de/home FAIR REMUNERATION: Remuneration is part of the EU funding program ‘Marie Sklodowska-Curie’ and depends on the personal
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related fields demonstrated expertise in one or more of the defined focus areas strong analytical and problem-solving skills, with experience in experimental design, data analysis, or computational modeling
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, or computational modeling strong communication skills, both written and verbal in English ability to work both independently and collaboratively in an interdisciplinary team commitment to responsible research 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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international project partners, embedded in an ERC-funded project. For deeper insights, please have a look at our institute website: https://www.fz-juelich.de/en/pgi/pgi-7 and the research group in which
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tasks: You will work together with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement
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presentations Participate actively in team meetings and research discussions. Your qualifications Currently enrolled in Computer Science, Data Science, Mathematics, or a related field Basic knowledge in machine