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PhD Scholarship Keep military drones hidden from enemies! This PhD develops cutting-edge stealth communication tech so UAVs can coordinate and sense their environment without ever revealing
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to: Enhancing Small-Signal Stability in Inverter-Dominated Grids, Examining the effectiveness and uptake of electricity pricing mechanisms, Forecasting the future of indoor air, Role of storage in the energy
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staff position within a Research Infrastructure? No Offer Description Based in School of Computer and Information Technology (Mawson Lakes) Full-time (1.0 FTE), 2-year fixed term with a possibility for +1
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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PhD Scholarship PhD Opportunity for electrical, telecommunications or computer engineers interested in applying their knowledge to advance quantum communications. The successful candidate will
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in finite element modelling and machine learning (desirable). How to apply Apply for this scholarship at the same time you apply for admission to QUT's Doctor of Philosophy . *The first step is to
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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with 1414 Degrees’ silicon based thermal energy storage technology, SiBrick®, to enable continuous hydrogen production from intermittent renewable electricity. The PhD student(s) will join the project
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outstanding domestic candidates for Master’s by Research or PhD study in all departments, within the Faculty of Engineering. These departments include: ● Chemical Engineering ● Civil Engineering ● Electrical