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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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. Application deadline: 22 June, 2025 For questions, please contact: Associate Professor Xin Zhao, Fluid Dynamics xin.zhao@chalmers.se *** Chalmers declines to consider all offers of further announcement
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 5 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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machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital co-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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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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dynamical systems. The position is part of the research project “A Rigorous Framework for Transient Random Dynamics”, funded by the Dutch Research Council (NWO). You will be part of a team with a PhD student
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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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