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Field
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software development. Experience applying large language models (LLMs) or autonomous agents to scientific tasks such as code generation, protocol reasoning, or automated experimental planning. Proven ability
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use of in vivo and in vitro inhalation exposure models to develop medical countermeasures against chemical threat agents. In addition, you will participate in research projects characterizing the toxic
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learning, including designing, developing and evaluating systems and models to enhance learning through AI technology. The Postdoc fellow will engage with developing AI-agents, models, frameworks and
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offered by agents. Focus on personalized support for the student and the teacher in various phases of the learning process. Modeling and Exploration of Emotional and Cognitive Profiles of Agents:Develop
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to be developed consists of: Architecture of Collaborative Agent Ecosystems with Human Interaction:Explore and develop architectures where different AI agents (based on LLMs) play distinct roles, such as
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creating and training a large language model tailored to the OMS context, integrating AI agents, and implementing a vehicle mobility interface. The platform will be tested, validated, and continually refined
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enrolled in a Master’s program and undertaking their Master’s dissertation within the scope of the Blockchain.pt project, specifically related to the Field Lab: Agent-Based Model: How can the behaviors and
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with NERSC staff, domain scientists, and partners at NVIDIA and Dell to prepare high-impact workflows for 12,000+ NERSC users. What You Will Do: Contribute to one or more NESAP AI-based scientific
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, energy systems optimisation, techno-economic forecasting, or agent-based modelling proficiency in scientific programming (preferably Julia, Python, or MATLAB) competence in data analysis and probabilistic
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, industrial decarbonisation, energy economics, or a related discipline demonstrated expertise in energy systems modelling, energy systems optimisation, techno-economic forecasting, or agent-based modelling