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. Basic Qualifications: A PhD in Materials Science & Engineering, Physics, Chemistry, or a related field completed within the last 5 years A minimum of 2 years of post-Ph.D. experience utilizing
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multiple sources. Experience developing reproducible analytical workflows and documentation. Demonstrable specialized communication skills: Proficient technical and scientific writing Publication record in
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. Experience with underground, off-road, subterranean, or other unstructured-environment robotics and field testing. Experience with Docker for containerization and deployment. A strong publication record in
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communication skills, a proven publication record, and effective interpersonal skills. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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related field completed within the last 5 years Good track record in scattering theory, quantum many-body theory, thermodynamics, statistical mechanics, or non-equilibrium physics. Experience in
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, usage and understanding of basic Machine Learning algorithms and tools. Solid record of productive research demonstrated by publications in peer-reviewed AI/NLP/ML conferences or journals, and/or open
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track record of productive and creative research proven by publications in peer-reviewed journals. Excellent written and oral communication skills. Motivated self-starter with the ability to work
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Demonstrated ability to conduct independent research with a good publication record Excellent written and verbal communication skills for interdisciplinary collaboration Commitment to ORNL’s core values: Impact