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Field
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generating a high-quality training dataset to support the development of the AI foundation model Contributing to the design and implementation of advanced deep learning architectures (e.g., Transformers, CNNs
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academic records (including transcripts) at masters level or equivalent degree level. • Creative and innovation potential, ability to think out of the box. • Motivation of the candidate for inter
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to co-design algorithms and circuits to develop efficient neuromorphic hardware, tailored to target tasks. In detail, you will: develop circuit-plausible training/inference algorithms and analyze in
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facilities (sequencing, proteomics and metabolomics). This dynamic setting fosters innovation and teamwork, enabling cutting-edge discoveries in the field of microbiome studies. The candidate will work on a
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website: https://www.isse.tu-clausthal.de/. Your tasks are Research and development in the above mentioned topics. Design and implementation of prototypes. Publication of your results at national and
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, we are at the forefront of innovation. Moreover, employing advanced techniques like artificial intelligence and machine learning, we are revolutionising material production, making it more efficient
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materials are iteratively optimised. Recycling, Sustainability and Life Cycle Analysis The successful and sustainable recycling of a battery cell begins with the design of the materials and the manufacture
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an international scientific conference Courses offered in this year’s Doctoral Summer School Theoretical Perspectives in Management Qualitative Research Methods Survey Design and Measurement in Social
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development of coupled techniques, methods, and tools existing in the group Collaboration with catalyst synthesis and theory groups to design advanced electrocatalysts using the knowledge obtained in
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field. Experimental skills in biophysics experiment design including associated data analysis. Prior knowledge of structural biology and associated data analysis techniques is of great advantage. Strong