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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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the Hadronic Physics Team, part of the Medium Energy Group in the Physics Division, comprising nine staff members, two engineers, and postdocs and students. Our diverse program includes leading electron
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this work we investigate how molecular materials coupled to solid-phase scaffolds may influence molecular motion, photoinduced kinetics, charge dynamics, and assembly durability. The work will target
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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research projects, data analysis, physics interpretations, and reporting of the results. A strong background in the field of Experimental Nuclear Physics. Ability to model Argonne’s core values of impact
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mechanistic studies of catalytic systems Strong written and oral communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Familiarity with ligand design
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model Argonne’s core values of impact, safety, respect, integrity, and teamwork Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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research groups. Skills for effective communications, verbally and through writing. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior