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chemical analysis methods (e.g., SEM, TEM, XRD, XPS, FTIR) Strong background in laboratory practices and data analysis Excellent written and verbal communication skills Demonstrated ability to work
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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-throughput workflows for data acquisition and analysis Contribute to on-the-fly data processing and integration with computational tools Collaborate with multidisciplinary teams in nanofabrication
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model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Experimental data analysis in hadronic physics Superconducting electronics and sensors Detector simulations
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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mechanisms through reaction kinetics analysis and other physical organic and inorganic techniques Perform detailed in situ / operando studies of catalysts using X-ray Absorption and Emission Spectroscopies
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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. The group develops modeling and optimization tools to accelerate the design, analysis, and deployment of efficient, flexible, and cost-effective industrial and energy processes. The postdoctoral researcher
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at Materials Engineering Research Facility (MERF) and collaborators inside and outside Argonne. The candidate is expected to design and conduct experiments, analyze data and explore mechanisms behind
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to develop, synthesize, characterize and electrochemically evaluate next generation cathode materials for lithium-ion and sodium-ion batteries. Position Requirements Recent or soon-to-be-completed PhD