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machine learning We offer: Academic freedom to pursue your scientific interests related to infection biology, inflammation, gene expression, and intracellular organization Competitive salary including
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applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
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-class graduates with expertise in the CRC-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very