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Your Job: Developing and implementing QC algorithms (QAA, QAOA, QSVM), quantum AI algorithms, use case adapted algorithms to test and benchmark latest technology focusing on gate-based QC Advancing
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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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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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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with several research groups working in related fields, particularly in algebraic geometry and algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 10 days ago
Experience in HPC computation (application and algorithm/code development) Willingness to closely collaborate with experimentalists and theoretician. Joint research approach of all ERC synergy team members
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project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance algorithmic justice through participatory design” (PARTIALJUSTICE) to examine issues of justice and participation in