855 computer-programmer-"https:"-"UCL" "https:" "https:" "Computer Vision Center" uni jobs in Germany
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software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new code via
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Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects
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Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects
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you contribute You are a registered student in a natural sciences degree programme. You show commitment and enjoy taking the initiative. Your enthusiasm for and curiosity about research drive you
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« What you contribute You are a registered student in a natural sciences degree programme. You demonstrate commitment and enjoy taking the initiative. Your enthusiasm and curiosity about research drive you
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Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented, young scientists the chance to work on cutting edge research
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« »Mathematics for vehicles, systems, and plants« »Analytics and computing« What you contribute You are a registered student in a natural sciences degree programme. You demonstrate commitment and enjoy taking
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interdisciplinary Programme Areas (PAs) which work collaboratively towards achieving ZMT’s mission. This position will be located in and contributing to PA2 - Global Change Impacts and Adaptation, which addresses
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sustainable use of tropical coastal ecosystems. To this end, we work in an inter- and transdisciplinary manner with our partners in the tropics. The ZMT is a member of the Leibniz Association. Program Area
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our group "Computer Vision and Machine Learning" in developing AI models and transferring them into production. In the master's thesis "Exploring latent spaces of deep networks for fault analysis in