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the following is required and should be clearly described in the personal letter: - Protein expression in prokaryotes and/or yeasts - Experience with multiple protein purification techniques
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be given to candidates with strong research background in mathematical statistics and machine learning, particularly generative modeling and sequence modeling. Candidates who have demonstrated
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improving material and energy systems across multiple applications, including: High-temperature corrosion prevention Development of advanced fuel cells Recycling of valuable materials Innovations in nuclear
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description and working tasks Linear algebra expressions are evaluated in an efficient and robust way by mapping them to a carefully chosen sequence of calls to optimized functions as offered by libraries
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research alignment with commercial objectives Participate in regular progress meetings and technical discussions with industry collaborators Contribute to the development and maintenance of open-source
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across multiple applications, including: High-temperature corrosion prevention Development of advanced fuel cells Recycling of valuable materials Innovations in nuclear energy Our collaborative and dynamic
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element simulations to create intelligent design tools Industry Collaboration and Utilization Work closely with startup partners to ensure research alignment with commercial objectives Participate in
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a doctoral degree and are expected to idearlly have at least two years of relevant experience in research or practice post-graduation. The degree should be in a discipline aligned with at least one of
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the orientation of various types of nanoparticles within both thermoset and thermoplastic polymer matrices. This position entails close collaboration with industrial partners to implement the alignment technique
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experiments (both in the lab and in the field), coordinating cross-cultural studies involving multiple international research groups, data analysis, computational modeling, and writing scientific articles