15 computer-algorithm-"CNRS" Postdoctoral positions at Forschungszentrum Jülich in Germany
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algorithms, preferably in the domain of QC, such as QAA and QAOA Experience in cloud computing and building cloud computing infrastructure Interest and/or experience in developing and conducting lectures and
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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, computational physics, statistical physics, non-equilibrium quantum many-body physics Ideally, experience with neural quantum states or other applications of machine learning methods in many-body physics
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existing quantitative methods in international nuclear safeguards with state-of-the-art artificial intelligence/machine learning (AI/ML) algorithms Contribute to standardising methodologies for calculating
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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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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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc.. You will be involved in all phases of this process. You will
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, computer scientists and physicists to combine our extensive expertise in neuroscience, imaging and AI into viable solutions Publish your results in high-quality scientific articles National and international
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degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural language processing (NLP), and fine-tuning techniques
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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