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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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of the Max Planck Society for the Advancement of Science. The Department of Machine Learning and Systems Biology , headed by Prof. Dr. Karsten Borgwardt, invites applications for a Postdoctoral Research Fellow
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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foundation models. The Successful Candidate Is Required To: • Contribute to research on post-training of LLMs. • Implement machine learning algorithms, experimental frameworks, and research prototypes
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fairness. • Develop and evaluate large language models, foundation models, and agentic AI systems. • Implement machine learning algorithms, experimental frameworks, and research prototypes
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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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multidisciplinary team of medicinal chemists, biochemists, cell biologists and other researchers. You will be responsible for applying computational chemistry, chemoinformatics and machine learning approaches to drug
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The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims