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Field
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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training an autonomous agent to ‘learn’ a control strategy. This formalism is similar to that of optimal control, with the difference that the agent does not have an explicit model of the dynamics
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-informed neural networks (PINNs) for integrating mechanistic constraints into ML frameworks, and creating LLM-based agents to assist with mechanistic model construction and knowledge curation. Track B
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, PyTorch, JAX etc. Experience with modern AI concepts such as large language models (LLMs), vision-language models (VLMs), model context protocol (MCPs), and the development of agentic AI tools. Skill in
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Are you passionate about deep learning, generative AI, agents? We are seeking a postdoctoral researcher to join the research group led by Ivan Titov ( http://ivan-titov.org/ ), part of the natural
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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Forecasting Agent-based Modelling and Simulation Data-driven Modelling Transportation Planning and Network Design Your profile Hold a PhD in applied mathematics or engineering Strong analytical and numerical
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modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics into their models; or2.Computational social scientists with experience in empirical research and/or theoretical
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) 4+ years’ experience in Matlab™/C++/Python 2+ years’ experience with acoustic modeling software (k-Wave, FOCUS, Field II) 2_ years’ formulating and characterizing nanoparticles or contrast agents
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candidates may include: 1.Energy modelers with expertise in integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics