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Field
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) department at Telecom Paris. Reinforcement learning (RL) has emerged as a useful paradigm for training agents to perform complex tasks. Model-based RL (MBRL), in particular, promises greater sample efficiency
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Perturb-seq, with our integrative analyses often employing computational approaches such as agent-based modeling to deconstruct gene-regulatory networks and predict system behaviors. As a postdoctoral
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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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-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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) 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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the model plant pathogens Botrytis cinerea and Phytophthora infestans we will investigate their immune reactions and evolutionary responses to experimental selection by biocontrol agents including
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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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: Title of Post: Post Doctoral Researcher (Level 1) AI-Minds Project: Trustworthy AI Large Language Educational Models JOB SYNOPSIS Post Doctoral Researcher to develop agentic LLMs tailored to immersive
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address scientific problems in pharmacology and medicine. Build and adapt AI-assisted tools (e.g., LLM-based agents) to support mechanistic model development and biomedical knowledge integration. Implement