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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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scientific journals and conferences Your Profile: A doctoral degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural
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for the production of heat pipe components Your Profile: Completed university degree in mechanical engineering, physics, materials science, computational engineering, or a related field, with a PhD or Master degree
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Design and implement optimization techniques for full-stack improvement of quantum algorithms Model major sources of experimental error for control theory or for error mitigation techniques Scientific
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genomic approaches Application of the modeling approaches in relevant downstream tasks Co-development of high-performance computing AI training codes for the first European Exascale Supercomputer JUPITER
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detail: Development of APIs for electrolysis systems and analysis devices Implementation of autonomous process control Conceptualization and implementation of degradation models for electrolysis Studying