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Commander . Preferred Record of scholarly publications and experience supporting research projects, including data analysis and grant preparation Experience with agent-based models, statistical methods
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. • Familiarity with MODFLOW, MATPOWER, OpenDSS, Machine Learning based emulators, or agent-based modeling. • Knowledge of scenario development, resilience frameworks, and socio-environmental-technological systems
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or mentoring others in automation and AI workflow development. Experience with large language models (LLMs), intelligent agents, and responsible AI frameworks. Strong consultative and evangelism skills with
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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-preserving models that implement synthetic data; and developing generative AI models for accelerating data sharing using synthetic data, agentic AI synthetic data, differential privacy, and federated learning
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. Expertise in Large Language Models (LLMs) and related frameworks (e.g., LangChain, Transformers) Proficiency in prompt engineering techniques for optimizing LLM performance Strong understanding of agentic AI
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fields: nonlinear PDEs, functional analysis, numerical analysis, PDE-based modeling and numerical simulations excellent command of the English language ability to teach in German and English We offer
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) and an agent-based reinforcement learning system can developed to identify and optimise safe journeys to reach affected forest plantations. The specific research objectives will be co-developed with
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, agent-based modeling, active transport modes mobility, and urban accessibility assessment models; c) In case the applicant is not a native speaker of Portuguese or English, they must have language skills
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carry out the doctoral thesis for the 26/27 academic year. Adoptive cell therapyagainst cancer is a type of immunotherapy that is based on the use of agents that enhance the immune cells of the patients