About this role
Joint Assistant Scientist position at Argonne National Laboratory to develop and apply AI/ML methods for autonomous, closed-loop synthesis of nanoscale and quantum materials, integrating synthesis with in situ/operando x-ray, electron, and optical characterization. Responsibilities include designing closed-loop experimental workflows, active learning and Bayesian optimization, generative/inverse-design modeling, multimodal data analysis with uncertainty quantification, and integration of edge and HPC data workflows.
Skills for this role
Artificial intelligence (AI)Machine learningActive learningBayesian optimizationGenerative modelsInverse designReinforcement learningAgentic AIDeep learningPyTorchTensorFlowJAXBoTorchGPyTorchscikit-learnPythonExperimental control systemsLab-automation frameworksROSBlueskyEPICSLaboratory automationRobotic synthesisMultimodal data analysisMultimodal data fusionReal-time data reductionUncertainty quantificationHigh-performance computing (HPC)Edge computingScientific data infrastructure