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of molecular and/or heterogeneous catalysts Strong understanding of kinetics and thermodynamics as applied to catalysis Knowledge of and experimental expertise in synthesis and characterization of highly air
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contributions in: Building novel generative models for predicting genome-scale evolutionary patterns using GenSLMs Developing scalable models that can, when integrated with high throughput molecular dynamics
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help
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The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee on the topic of CFD modeling of internal combustion engines fueled by low-carbon fuels
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qubit-based quantum processors and connect them via a campus-scale fiber-optic network. The postdocs will design and fabricate superconducting transmon qubits and microwave-optical quantum transducers and
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at the APS, integrating x-ray optics and wave propagation models with realistic sample simulations based on dislocation dynamics and molecular dynamics of relevant materials. Significant attention needs
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) at Argonne National Lab (near Chicago, USA). The postdoctoral researcher will work on the development of large-scale molecular dynamics, AI and machine learning based analysis to understand ferroelectric
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transition metal complexes, donor-acceptor pairs, and hybrid molecular-material interfaces. By designing and deploying state-of-the-art ultrafast nonlinear optical spectroscopy techniques—such as transient
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platforms, with collaborations with the Argonne Leadership Computing Facility and the Advanced Photon Source. This postdoc will contribute to the design and implementation of a software infrastructure for the