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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 4 days ago
an internationally recognized, federally funded research program in materials synthesis. Experience with data-driven and AI/machine learning methods to guide or enhance synthetic research objectives is desirable
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of solar energy systems, applying machine learning methods, and data analysis. A background can be in materials engineering, physics, electrical engineering, computer science, or another suitable field. In
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methods and procedures and ensure correctness of work. Budget for, and coordinate, public events and other related programs; develop and coordinate new ideas and concepts for program themes, materials and
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Minimum Qualifications: Ph.D. in Materials Science, Physics, Chemistry, Mechanical Engineering, or related fields Preferred Qualifications: Strong expertise in atomic-scale simulations (e.g., MD, DFT, ML-FF
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office suite and website management. 5. Experience in designing marketing and communications materials, including print, web, digital and social media 6. Ability to supervise, plan, and execute program
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which you would enhance the educational experience of students and further the College's educational goals . The Physics Department (https://www.hamilton.edu/academics/departments/physics ) has eight
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topological quantum materials. Our group aims to discover new topological quantum phases of matter, explore their physics and apply them to address challenges in electronics, photonics, quantum computing
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of materials, mechanical materials), advanced process engineering (process integration, advanced materials and devices), life sciences (biomaterials, biomedical engineering), and related areas in the field
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whose research engages with physical interfaces, new materials for interaction, exploratory device construction, and the wider space of computational making. Areas of interest include experimental
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD student will take place inside LGP2 (Process Engineering Laboratory