55 programming-language-"FEMTO-ST"-"FEMTO-ST" Postdoctoral positions at Argonne in United States
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experience with the application of multiphysics modeling to model complex physical phenomena. Strong interpersonal, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact
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with applying unsupervised ML algorithms such as autoencoders, clustering, to time-series data is preferred Experience with the data from HEP experiments is strongly required Programming expertise in
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completed in a relevant field of study. Experience with deep learning (DL) frameworks such as PyTorch, TensorFlow, or JAX. Strong programming proficiency in Python. Demonstrated experience with coherent X-ray
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instrumentation and experiments. Proficiency in scientific programming and data analysis (Python preferred; experience with NumPy/SciPy, Jupyter, version control). Experience with C/C++ or MATLAB is a plus
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. Familiarity with total scattering/PDF techniques and related software. Hands-on experience with lasers, timing/synchronization, or detector systems. Scientific programming skills (e.g., Python) for data
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TEM specimen preparation via FIB and/or nanofabrication techniques (photolithography, e-beam lithography) Proficiency in programming (e.g., Python) for experiment automation and/or image analysis
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to the development of new research directions aligned with program goals. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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the domains of environmental, water, and energy system analysis. Prepares reports, papers, and presentations for conferences, workshops, and technical journals. Supports program development including
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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