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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data. You will work at the frontier of active learning and ML-guided
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generalizability, reliability, and robustness. Prof. Li has authored over 40 papers in top-tier AI and machine learning conferences and journals. Ranked among the Top 50 researchers in “Spatiotemporal Data Mining
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need, this may be prepared from published field operation data, laboratory measurement or other sources. Machine learning can be used to select the bet data set for each particular cases covering
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
31.07.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, is inviting applications for a fully funded PhD position at the Technical University
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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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at the Medical Faculty of Heidelberg University, in collaboration with Prof. Dr. Irmela Jeremias, invites applications for a PhD student in Bioinformatics / Computational Biology as part of the CRC1709-funded
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information about the role, please contact Prof. Radu State Your profile Strong background in AI, machine learning, or multi-agent systems, ideally with interest in financial systems, decentralized ledgers
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1