77 electrical-engineering-coding-theory PhD positions at RMIT University in Australia
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PhD Scholarship in Integrated Photonics for Telecommunication, Biosensing and Precision Measurements
Bachelor/Masters degree (or equivalent) in electrical/electronic engineering, nano/microfabrication, physics (optical) or a field related to the desired skills listed below, with a high level of academic
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in an applied engineering environment. Desired skills Excellent mathematical and programming skills, including experience creating effective code in Python, R and Matlab. Knowledge of chemistry and
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description of how these proteins respond to physiological stimuli to control electrical signalling the body. This project, in collaboration with researchers at Cornell University, USA, is funded by
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engineering, materials science, chemistry, and engineering. This project relies on polymer science and synthetic chemistry to design the novel polymer chemistry and nanofibre structures for advanced membrane
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materials based polymer/elastomer composite development for 3D printing of tyre tread represents the biggest knowledge gap in the current developmental cycle. The aim of this project is to develop a robust
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) scholarship available Must meet all entrance requirements for the RMIT Aerospace Engineering PhD programme including any visa requirements. Must meet all entrance requirements for the RMIT Aerospace Engineering
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, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering backgrounds can also apply. To be eligible for this scholarship, you must: Meet
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Are you an Australian PR, citizen, or an international student in Australia with a 1st class Honours in Chem/Mech Engineering, Physics, or Maths? RMIT Engineering PhD candidates get a laptop, world
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physics, chemistry or related engineering disciplines are encouraged to apply. To be eligible for this scholarship you must: have a first-class honours or equivalent in physics, chemistry, or related
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about future states of species populations and ecological communities. The project will explore the application of dynamical point process models from probability theory to ecology so as to determine