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Field
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Developing computational models and running computer simulations in science and engineering still requires substantial expert knowledge. Agentic artificial intelligence (AI) offers a great
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responsibilities will include: Identification of key microbial species in Antarctic coastal sediments using network analyses Investigation of the genetic repertoire of these key species to elucidate their eco
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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philosophy and/or social studies of science and technology. The position is part of the Horizon MSCA Doctoral Network “Towards sustainable computational fluid dynamics” coordinated by the Institut National
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be advantageous: Experience with scientific expeditions Experience in computer-aided analysis of biological sequence datasets (e.g., with R, Python and Bash/Linux environments) Basic understanding
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Engineering Computer Engineering Physics Mechatronics Information Engineering or a related field. Ideally, you have experience in several of the following areas: Electronic circuit or measurement system
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) is one of the world-leading groups in the field of computer simulations of active, soft and living matter systems, such as cells, bacteria, tissues, and active synthetic colloids. Our aim is to provide
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computer simulations Working in close collaboration with theoretical physicists to test models and develop new insights Your Profile Bachelor's degree in physics Master’s degree/diploma in condensed matter
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Support programs equity Fields of action Networks for equity Contact Team Equity News and publications Back Press releases attempto online Newsletter Uni Tübingen aktuell University of Tübingen magazine
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17.05.2026, Academic staff In networks of robots and unmanned aerial vehicles, the ability to exactly coordinate the observations of the different devices is key for successfully carrying out