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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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. Education: Ph.D. (< 5 yrs. since Ph.D.) • Familiarity with image processing and simulation software. • (Preferred) Experience with nanofabrication, transport measurements, thin film deposition, in-situ TEM
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oscillators driven by the storage-ring RF signals to fulfill the function of manipulating X-ray pulses. More specific responsibilities include MEMS design and simulation, testing and characterization
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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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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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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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be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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simulation laboratory as well as supporting ongoing DOE projects. Candidates will be required to work in at least 4 of the following areas: Develop a functioning test bed using Opal-RT PHIL real-time platform