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Field
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machine learning (ML) along with data from previously solved problem instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Newton`s method. In
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Optimization (DPO) and reinforcement learning from human feedback, building preference datasets together with clinicians - Build and run a Red Team process with physicians, computer scientists, and patient
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image data analysis A willingness to engage in interdisciplinary scientific work
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comparable, relevant field of study Understanding of the fundamental concepts and techniques of Artificial Intelligence (AI) and Machine Learning (ML) Knowledge in specific AI application areas such as Natural
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silico approaches. This may include mathematical modeling of biological systems, machine learning and artificial intelligence methods, and the development of innovative algorithms and software pipelines
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Max Planck Institute for Intelligent Systems, Stuttgart, Stuttgart | Stuttgart, Baden W rttemberg | Germany | 22 days ago
Job Code: Stu_121 Job Offer from March 27, 2026 The Max Planck Institute for Intelligent Systems (MPI-IS) conducts research on intelligent systems that perceive, learn, and interact. Through
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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fields of expertise that complement the Faculty’s research in the humanities and social sciences in the following areas: human-machine interaction; AI usability; accessible and inclusive AI; AI ethics