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researcher should have expertise in materials/mechanical/electrical engineering with an excellent understanding of fluid mechanics as well as experience with Arduino/Raspberry Pi programming, 3D printing and
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training students Maintain analytical equipment Cooperate with other large collaborative projects of the research group Qualification: Required: A diploma and a PhD in microbial natural product chemistry
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 7 hours ago
@orau.org Qualifications The successful applicant should have a PhD in science or engineering discipline with experience in running reacting fluid dynamics simulations. Experience with high fidelity, state
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control, from combinations of computational fluid dynamics and experimental data. You will join the Australian Centre for Robotics (ACFR), at the University of Sydney. The ACFR is one of the largest
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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should have: Demonstrated experience with computational fluid dynamics (CFD) is required. Experience with computer aided design (CAD) tools would be an asset. Experience with programming and scripting
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materials relevant to thermal energy storage, including conducting structural characterizations and studying their thermophysical properties. Proficiency in computational fluid dynamics (CFD) simulation
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research areas relevant to the project: solar magnetic field modelling, computational fluid dynamics, or solar observational data analysis. Working knowledge of at least one scientific computing environment
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the Department of Radiology at Stony Brook University. The successful candidate will lead efforts to quantify multi-scale neurofluid dynamics, including blood flow and cerebrospinal fluid movement, using state