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understating of the fundamental process of organellar replication, insights gained from this work will aid downstream translational projects of chloroplast engineering to develop crops with better traits
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Astrophysics, Space Physics, Aerospace Engineering, Applied Physics, or a closely related field. Previous experience with numerical modelling and simulation relevant to space systems of astrophysics and a
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emulator to demonstrate the feasibility of the new signalling/waveform. The ideal candidate for this project would have first degree and MSc/MEng in physics, electronic and electrical engineering or a
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. You should apply if You have a PhD in Theoretical Physics or Philosophy of Physics You have at least an undergraduate degree (joint or single honours) in Mathematics or Physics You have advanced
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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University
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, ensemble Kalman filters, and physics-informed neural networks (PINNs) enforce conservation laws while fitting observations. The key is to apply the vast amount of physical insights developed in turbulence
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PolyU’s website at https://www.polyu.edu.hk/ . DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING Research Assistant Professor in Smart Manufacturing Systems / Physical AI / Embodied Intelligence (three posts
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-dependent MLCS regulation on lysosomal trafficking, mitochondrial quality control and hypoxia-induced cell death. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd
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candidates for this project should have a strong background in Applied Mathematics, Engineering, Physics or other related disciplines. Full details of how to apply can be found at the following link: https
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Information on the Particle Physics group in Sheffield and our projects can be found here: https://www.sheffield.ac.uk/mps/research/physics/particle Funding Notes This project is for Self-funded students