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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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of impact, safety, respect, integrity, and teamwork. This level of knowledge is typically achieved through a formal education in materials science, physics or related discipline at the PhD level or
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policy, environmental science, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven
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PhD (typically completed within the last 0-5 years) in pyrometallurgy, chemistry, materials science, chemical engineering, or related scientific background with 0-3 years’ experience. Experience in
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change on new architectures will be a key focus. Position Requirements Required skills, knowledge and experience: A recently completed (within the last 0-5 years) or soon-to-be completed PhD. in
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publishing research findings. The project will be conducted in close collaboration with scientists within a team. Position Requirements Required skills and experience: Completed PhD (typically completed within
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management
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: 10.1038/s41467-023-39984-3 Position Requirements This level of knowledge is typically achieved through a formal education in Physics, or a related field at the PhD level with zero to five years
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation