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opportunity to establish a cutting-edge research program with significant impacts in this field. We are particularly interested in candidates who can develop an innovative research agenda in areas such as
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program) by e-mail (in a single PDF file) by 15.06.2025 to: info@isse.tu-clausthal.de Please do not hesitate to contact us if you have any questions. We look forward to hearing from you! Please note our
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among employees, we offer an extensive sports programme with over 100 different sports, as well as a fitness centre with a sauna and climbing space. Health management measures, such as courses
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program, colloquia, workshops). Your tasks Processing and analyzing text-based data from learning management systems, assessment systems and qualitative data sources such as interview transcripts
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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Description Within the Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) we are currently seeking to recruit, as soon as possible, a Doctoral Researcher (f/m/d – 75 %) in Mathematics for the project “Quantized vortices and nonlinear waves” The CRC has been funded...
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interested in working at the boundaries of several research domains Master's degree in computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline
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least one of areas like animal communication research, probabilistic modeling, or language evolution is a strong requirement. As the position involves computational / mathematical modeling in the form
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to work in a team and in a research network • Computer programming experience • Knowledge in electronics • Experience in the field of optics and quantum optics is desirable We offer: • A truly unique
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training