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Field
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software
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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
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interested in theory-practice transfer and like to work collaboratively. Relevant publications in scientific journals and at conferences complete your portfolio. What we offer Salary according to Bavarian
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Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, Entrepreneurship Theory & Practice, and Journal of Business Venturing, Journal of Product Innovation Management
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
are searching for outstanding candidates, with a successful degree (master/ diploma/doctoral/PhD) with exceptional records. A strong disciplinary background in • control, system theory and optimization • machine
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sensors and apply them to novel applications. Technically, your work will involve the design and construction of optics and electronics, clean room fabrication and software development, as well as theory
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strong publication history, including but not limited to conferences such as MICCAI, NeurIPS, ISBI, ICCV, ICML, ECCV, or others. Fluent familiarity with at least one coding language for ML or data analysis
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algorithms, mechatronics, intelligent robotics and prosthetics, robot learning algorithms, foundations of machine intelligence, as well as nonlinear control and systems theory. Furthermore, we offer unified
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, methods, and algorithms into existing high-performance frameworks, the fast prototyping of new ideas in individual code, an interest in the entire simulation pipeline: starting from simple algorithms