132 programming-languages-"the"-"CNRS"-"Washington-University-in-St"-"U" positions at Technical University of Denmark in Denmark
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documented prior experience with either biosynthesis or electrochemistry, or both. The ideal candidate is a good communicator in both written and spoken English, is independent, and enjoys collaborating with
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Job Description Do you want to grow as a scientist and become a microbiome researcher at the best technical university in Europe? Do you want to hone your scientific skills and use programming
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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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English skills. You should strive towards scientific excellence and be ambitious and hard-working. The preferred candidate shall have background / experience in the following areas: Solid Mechanics
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microbiology and CMDs. You need to be ambitious, motivated, capable of working independently, and have good skills within written and spoken English. In addition, you should have experience with experimental
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Identification System (AIS) for ship detection. You must be fluent in English, both speaking and writing and possess excellent communication skills. As part of the Danish Ph.D. program, you will follow a number of
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mindset, be curious and eager to learn. Since you will join an international group, a good command of written and spoken English is necessary. Your academic background should include a Master degree (or
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requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment will be made by Associate Professor Christian Damsgaard, Professor Jakob
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collaborations, strive toward scientific excellence, be highly motivated, ambitious, and hard-working. Good communication skills in written and spoken English are required. The groups are ambitious and strive
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. Responsibilities and qualifications The overall aim of the project is to generate new knowledge about how emerging generative AI tools – such as Copilot, speech-to-text systems and retrieval-augmented generation