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Laboratory’s Biosciences Division, allowing for seamless computational and experimental research integration Position Requirements A recent or soon to be completed PhD within the last 0-5 years Computational
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer
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. Position Requirements PhD completed in the past 5 years or soon-to-be completed in physics or related field. Strong knowledge of coherent imaging, light modulation, Fourier-domain signal processing, X-ray
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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: Cover letter describing your background, interests, and fit for the position. Curriculum vitae, including a list of publications. Contact information for three professional references. Application review
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and is based at Argonne National Laboratory (Lemont, Illinois). Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in high energy physics, or a related field Experience
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer science
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of our applications. Benefit to ALCF: This postdoc position will help ALCF evaluate and integrate data infrastructure needed to better facilitate AI models, including training, fine-tuning and inferencing