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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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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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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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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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, 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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templates for distributed AI training, agentic AI with modeling and simulation, and end-to-end workflow monitoring, profiling, and optimization. Working with quantum simulation tools, including NVIDIA CUDA-Q
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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
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Behavioral Algorithms of Pursuit Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is
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the economic benefits for individuals and communities when interacting with the energy markets. AUTONOMY will pioneer a novel transfer learning approach to exchange expert knowledge amongst energy manager agents
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for other critical illnesses including trauma, neurologic emergencies, sepsis, acute respiratory distress syndrome and heart failure. This is a 2-year position with an option to extend based on performance