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of generative AI algorithms for manufacturing Collaborate with an interdisciplinary team to transform research results into innovative solutions Develop high-quality code and build the basis for our industrial AI
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interested in current political and societal discussions Be able to work independently, manage multiple tasks and deadlines Be a team player with strong communication skills Have experience with coding (e.g
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have a strong background in quantitative methods and are excited to code. You are interested in topics of global poverty and inequality. You have a good knowledge of the statistical software R and/or
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, perform the evaluations hand-in-hand with the domain experts, and eventually release open-source code and the associated documentation, write research papers or technical reports as appropriate, and
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. Profile Enrollment as a student at ETH Zurich or the University of Zurich in a relevant field, such as computer science, engineering, economics and mathematics Intermediate coding skills in R, Stata
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on such hardware. Several technologies are considered for running on GPUs, compiler directives which are inserted in the code, or for some parts a complete re-write using a Python domain specific language (DSL
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economy, game studies, and/or code studies – would be welcomed. Also desirable would be experience (or interest) in local and global community building, academic and para-academic event organization, and/or
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researchers in coding experiments and other projects. Successful candidates will have a basic understanding of the programming paradigm, will be able to debug code with little assistance, be a problem solver
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manufacturing processes (APIs, excipients, intermediates). Intermediate coding skills in Python. Interest in data-driven research with policy impact. Workplace Workplace We offer Your job with impact: Become part
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learning technologies. You will actively participate in code reviews and maintain comprehensive documentation to ensure code quality and reproducibility. Additionally, you may be expected to contribute