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Researchers in AI-driven atomistic modeling and AI-accelerated cheminformatics to join the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), hosted by the Department of Chemistry and Materials
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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, Applied Mathematics, or a related field. Strong expertise in: Computer vision and image processing Deep learning (e.g., PyTorch, TensorFlow) Data-driven modeling and analysis Proficiency in Python and
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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ETH Zurich, we aim to understand how materials deform, degrade, break, and ultimately fail. Our research is driven by curiosity about the physical mechanisms that underlie failure and by the ambition
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, collaborative research environment Excellent verbal and written communication skills Preferred Qualifications: Experience working with manufacturing, materials, and sensor data Experience with real-time
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modeling, multimodal data fusion, interpretable machine learning, NLP, text mining, or automated extraction of materials data from the literature Experience with workflow automation, data infrastructure
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-informed or data-driven (AI/ML) manufacturing approaches Demonstrated ability to work effectively in collaborative research environments Does this position have supervisory responsibilities? No Preferred
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-informed or data-driven (AI/ML) manufacturing approaches Demonstrated ability to work effectively in collaborative research environments Does this position have supervisory responsibilities? No Preferred