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one of the following areas: mathematical methods, analysis and numerical aspects of machine learning, optimal transport, data science, harmonic analysis, or applications in biology and medicine
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and quantum computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a mathematical perspective? Are you an innovative and productive team player who enjoys being
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quantum many-body physics through the lens of quantum information and quantum computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a mathematical perspective? Are
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scientists who are active in the development of mathematical models or numerical methods in partial differential equations, in connection with uncertainty or data science. Specific fields of interest include
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English Desirable qualifications Research experience in HCI, Responsible AI, Social Computing, or a related area Experience with one or more relevant methods mentioned above Interest in interdisciplinary
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Other Graz, Austria Apply University of Graz, Austria Department of Mathematics and Scientific Computing Heinrichstrasse 36 8010 Graz Austria The address could not be found. Your Responsibilities
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Computing. Example topics for the group include how people understand and respond to technological harm, and how organizations can build responsible AI into the innovation process. We use a mixed-methods
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methods for chemical discovery and molecular design. These methods include machine-learned interatomic potentials, data-efficient and uncertainty-aware modeling, enhanced sampling, and statistical
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responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI
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AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including