39 programming-"the"-"DAAD"-"EURAXESS"-"U"-"FEMTO-ST"-"UCL"-"Prof" positions at Argonne
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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-augmented AI tools Interfacing AI tools with experimental facilities at CNM and Argonne Key Responsibilities Research leadership (50%) Develop and lead an independent and collaborative research program in
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research proposal outlining a two-year self-directed research program, including a description of how it builds on the applicant's current research and interests References After you apply, you will receive
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community In addition, the Group Leader is expected to develop and lead a world-class research program that strongly aligns with DOE priorities in low-energy nuclear physics, as articulated in the 2023
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electrocatalyst materials Plan and execute in situ/operando studies using advanced techniques such as X-ray Absorption Spectroscopy (XAS), X-ray Photoelectron Spectroscopy (XPS), Raman spectroscopy, Differential
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
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campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights
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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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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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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy