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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be complemented by own lab testing e.g., SSRT incl
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-dyncam.de . We are looking for highly motivated, enthusiastic, and team-oriented candidates that are eager to learn new methods, are passionate about science, and hold a master’s degree or equivalent in
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theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to apply new methods. For an initial
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independently and as part of a multi-disciplinary team a strong interest to acquire biological knowledge and work together with life scientists very good communication skills in English Are you interested? Then
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/or spatial multiomics, advanced imaging, iPS cells, machine learning, and computational biology. The ideal candidate will have a passion for addressing fundamental questions in biology and an eagerness
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and cutting-edge teaching methodologies. We are currently starting an innovative project that leverages eye-tracking technology to gain deeper insights into how medical students learn and to enhance
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of spoken and written English, communication skills as well as team spirit are essential. German language skills are not a requirement, but a willingness to learn is desirable. As the project involves work
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strategies - Model Proficiency and Application #learn the biophysical crop simulation model EPIC or an equivalent alternative #apply the model to simulate existing land management systems and land use change
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-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this project, we highly