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interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental design, and agent-based modeling to address problems in
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analysis of classical problems in numerical analysis in the framework of modern algorithms of machine learning. Our ideal candidate will have prior exposure to modern developments in theoretical machine
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surfaces machine learning methods, and/or the development of novel solutions to the many-body Schrödinger equation. Applicants with proven experience in the development of new computational methods and their
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"Urban Development & Mobility Transformation" focuses on researching and applying innovative tools and methods for sustainable urban development and the integrated planning of mobility systems. For our
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welcome applications from all areas of the life sciences, but especially those in tissue-scale and developmental biology, chromatin, RNA and chromosome biology, and synthetic/computational methods
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and determination? We are currently seeking a/an Technician / Data Manager 39 Faculty of Computer Science Job vacancy starting: 01.09.2025 (MM-DD-YYYY) | Working hours: 30.00 | Classification CBA
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, hydrology, environmental science, or a related field. Experience or strong interest in experimental and numerical geophysical methods and quantitative data analysis is especially welcome. The successful
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an outstanding research profile in applied or computational PDEs, who apply their expertise to address contemporary societal challenges. Areas of application may include, but are not limited to, climate modeling
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to the above requirements • Strong background in optimization and partial differential equations • Strong background in numerical mathematics and computing • Machine learning skills are welcome • English skills
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developmental biology, chromatin, RNA and chromosome biology, and synthetic/computational methods (including AI/ML) that will address complex biological questions from a mechanistic angle. Together with IMP, GMI