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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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-source software development, and with interdisciplinary collaboration is meriting. Publications at top machine learning conferences (ICLR, ICML, NeurIPS, AISTATS, etc.) or in leading physics journals
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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doctoral thesis (or weblink). Names and contact information (e-mail and telephone) to two reference persons who have agreed to act as reference for you. Please also describe the relationship with that person