38 phd-rehabilitation-engineering-computer-science Fellowship positions at Monash University
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#1 Chemical Engineering Department at Monash University and be part of a pioneering research initiative at the intersection of materials science, automation, and artificial intelligence. As a
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. We are currently seeking a Research Fellow with experience in AI and machine learning research and development, with a focus on any or all of following application areas: Computer vision Generative AI
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the University’s research capacity in a globally relevant field. The role provides the opportunity to develop and publish a monograph based on Korean Studies-related PhD research or, if already published
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₂ uptake efficiency, and the engineering performance of novel concrete systems. You will: Investigate zeolite synthesis and CO₂ adsorption via lab-on-chip platform Evaluate the mechanical and durability
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an interdisciplinary, purpose-driven team. You have: A postgraduate qualification in Computer Science, Data Science or related field Extensive experience working with large-scale, high-frequency (waveform) data
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for Health Economics is seeking a Level A Research Fellow to play a key role in an ongoing research program examining the effectiveness and cost-effectiveness of behavioural interventions, with a particular
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engineering. Be part of ARMI’s mission to address the unanswered questions with a multi-centre, cross disciplinary and highly focused approach, for the development of innovative clinical protocols as
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peer-reviewed publications, while providing senior-level expertise to support and mentor internal teams. A vital responsibility includes guiding emerging science-practitioners (Clinical Psychology PhD
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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management
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the guidance of artificial intelligence techniques. The project will develop novel design processes that embed material behaviour within agent-based and machine learning computational design systems