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synchrotron techniques and analysis of multimodal datasets Experience in material synthesis and characterization Demonstrated knowledge of general analytical methods and experimental practices Excellent written
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work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is
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-based and AI/ML approaches. This position focuses on high-resolution Earth system modeling and the analysis of convective storms and weather and hydrological hazards to improve predictability
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-throughput laboratory systems Proficiency in Python or similar programming languages for data processing, statistical analysis, and integration with AI/ML tools Excellent written and verbal communication
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extraction and analysis of sequencing-based omics data. Experience in bioreactor configuration, inline/online sensor integration, and PID-based process control; familiarity with bioreactor automation systems
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techniques and strategies for electrochemical measurements and post-mortem analysis. Write reports and high impact papers, and present research at conferences. Develop or support the development
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battery systems using techniques such as: thermogravimetric analysis (TGA) TGA-mass spectrometry (TGA-MS) and related methods Broad understanding of materials science concepts relevant to electrochemical
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or biological systems. The candidate will work in a multidisciplinary team, including physicists, biologists, and engineers, and will lead the effort in multimodal data analysis at the APS beamlines. May be
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cryogenic environments Participate in synchrotron-based characterization and data analysis Contribute to high-impact publications, internal reports, and scientific presentations at conferences and workshops
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on the LLM/agent and HCI layers of IDEAS, including: Mixed-initiative AI assistants for visualization and analysis, Natural interaction paradigms for scientific workflows, Integration of agentic systems with