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GESIS - Leibniz Institut für Sozialwissenschaften | Mannheim, Baden W rttemberg | Germany | about 2 months ago
used multilingual answer scales (original language, tested/validated translations from existing studies, meta-information) and make it available to the community. The collaboration is interdisciplinary
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and labs, e.g., a unique lab with variable acoustics (see demos on YouTube channel: https://www.youtube.com/@signalprocessingunioldenbu1018 ) Your tasks conduct research on speech enhancement algorithms
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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areas: + Quantum computing and quantum algorithms + Solid-state physics, computational materials science, or quantum chemistry + Battery materials modeling Excellent programming skills (e.g., Python) and
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applying machine learning algorithms for solving problems in protein engineering. Written and oral command of English is essential. Research environment The Max Planck Institute of Biochemistry, Martinsried
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the next era of the quantum revolution. Together, we research, develop, and design innovative quantum algorithms that push the boundaries of what is possible- especially in the natural sciences such as
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-based tiles can be arranged and actuated to form tunable metapixels, enabling dynamic control of light at the nanoscale. This project will integrate algorithmic self-assembly and nanomechanical switching
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2027 for 19,5 hours per week. The research associate will be working in project “AGEAI: Ageism in AI: new forms of age discrimination and exclusion in the era of algorithms and artificial intelligence
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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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, hardware-adapted optimization, and error mitigation techniques, aiming to identify requirements, limitations, and pathways for improvement of both hardware and algorithms - analyze variational ansatz