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algorithms for large-scale or distributed training/Robustness, fairness, and personalization in multi-agent learning/Training efficiency and communication reduction/Distributed training of transformer models
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-motivation and interest to learn new skills Great to have: Experience programming in Python, Julia, or C/C++ Experience with Mathematica Experience with finite element methods, agent-based simulations, and/or
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to reason about software (e.g., LLM agents for finding and fixing bugs)Static and dynamic program analysis (e.g., to infer specifications)Test input generation (e.g., to compare the behavior of old and new
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waves Agentic frameworks (e.g. LLMs with tool-use) for closed-loop idea generation for physics Other projects are certainly possible too. In general, we believe that building autonomous scientific systems
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), mathematical evolutionary modeling (game theory, dynamical systems, agent-based simulations or other), bespoke probabilistic modeling / (Bayesian) data analysis (e.g., in the Rational Speech Act framework
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Project The PhD project DC7 aims to develop and apply a coupled Agent-Based Model (ABM) and couple it to the Regional Flood Model (RFM) to evaluate the effect of adaptive behaviour of small and medium-sized
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experiments Previous experience with quantitative MRI, contrast agents, and cell tracking/labelling is beneficial High motivation for scientific work and willingness to contribute to an interdisciplinary team
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relevance. Your Tasks Antibody–Drug Conjugates (ADCs) are a rapidly advancing class of cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic agents. Upon
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. Treiber, the existing “Intelligent Agent Model” (IAM) for directional disordered traffic flow will be generalized to meet the above objectives (working name IAM2d). The main task is to simulate and
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with