753 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "UNIV" positions in Denmark
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guidance. Relevant example tasks here are: preparation of hardware setups based on microcontrollers, Raspberry Pi, etc. for teaching and research projects, programming and software tasks, e.g. creating
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ecological data collection. The positions focus on improving detection and classification performance of deep learning models applied to millions of images collected in European monitoring programs. Key
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also advanced scanners at our disposal. The department has overall responsibility for the Master's degree programs in medicine and in molecular medicine. At the department we are approx. 670 academic
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mathematics, or a related field. The candidates for the PhD position will be assessed on the following criteria: Strong skills in probabilistic modelling, machine learning, or simulation techniques. Programming
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relating to 19th-century science. Experience with archival work and/or knowledge of Scandinavian languages is an advantage, though not a requirement. Please include a research plan (max. 1000 words
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characteristics: be self-motivated, having a can-do attitude, willing to learn be able to program in C plusplus; ; and/or Python be at least familiar with ROS2 and Linux have decent understanding of robotics
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to develop an independent and competitive research program. Research areas of particular interest include, but are not limited to: Surface-sensitive vibrational spectroscopy (e.g. sum-frequency generation
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of programming (in particular Python) is preferred. Furthermore, the candidate should be highly motivated and willing to work in a team. Good communication skills in both spoken and written English, are a
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Job Description DTU Talent Partner is a program for larger engineering corporations in Denmark. Each partner can participate in 4+ events annually focused on Employer Branding, Recruitment, and
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming