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, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory or instrument responsibilities
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contribute to practical supervisory implementation Your Profile: Enrolment in a Ph.D. programme or Ph.D degree or Masters with 3-4 years of relevant professional experience in Economics, Sustainable Finance
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media technology programming) Mobile working option (hybrid), subsidy towards the Deutschlandticket as a job ticket, occupational health management (OHM) Reconciliation of work and family life, family
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Opportunities for personal and professional development Interesting, varied and challenging tasks and family-friendly working conditions Company pension plan (VBL) Company health promotion and the opportunity
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highly desirable. Benefits Career Development Postdoc program, scientific training & career center with tailored offers Recreation 30 days annual leave, flexi days, plus public holidays International Staff
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or related fields programming experience in Python or extensive experience in another high-level programming language is a prerequisite experience in geospatial data science, remote sensing, GIS, and open
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climate research, a forward-looking area with social significance 30 vacation days + additional time off at Christmas Eve and New Year's Eve Company pension plan and capital-forming benefits The position is
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Experience in energy storage Experience with programming languages (ideally Python) Fluent in written and spoken English Very independent and self-motivated way of working but also excellent teamwork skills
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At the University
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
related field # Proficiency in programming languages (Python, C/C++, Julia) # Background in machine learning methods # Experience in developing, training, and tuning machine learning models # Prior exposure