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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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to substantially advance this new qubit platform by realizing high-fidelity two-qubit gates. The postdoc will design single electron qubit devices, fabricate them in CNM cleanroom, and characterize them in CNM
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with data analysis and technical documentation; and contributing to publications, reports, and sponsor deliverables. The successful candidate will work closely with staff researchers and technical teams
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photonic quantum devices for a heterogeneous quantum network, including but not limited to superconducting qubits, microwave-optical quantum transducers, etc. The postdocs will design the devices, fabricate
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, we encourage applicants to consider how their data processing and software development capability fits into the proposed work and future direction. The Postdocs will be working directly with assigned
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, we encourage applicants to consider how their data processing and software development capability fits into the proposed work and future direction. The Postdocs will be working directly with assigned
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cheminformatics or polymer informatics, molecular representations, descriptor engineering, RDKit, characterization-informed modeling, multimodal data fusion, interpretable machine learning, NLP, text mining
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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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quantum transduction and terahertz (THz) photon generation via enhanced light–matter interactions. The postdoc will lead efforts in device patterning and the integration of complex materials—such as