27 postdoc-computational-biomedical-engineering Fellowship positions at Monash University in Australia
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Research Fellow - Environmental Informatics Hub Job No.: 680160 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment (with the possibility of an additional 2
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project with real clinical potential The Opportunity Are you a highly motivated and technically proficient researcher with expertise in electrochemical sensor development and biomedical engineering? We
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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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fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
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optimization, and covalent drug design. Collaborating with researchers and engineers at the Monash Institute of Pharmaceutical Sciences and QDX Technologies to implement scalable AI–quantum hybrid platforms
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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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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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preparation, and data analysis Assist in systematic reviews and grant development What you’ll bring: An honours degree or higher in a biomedical, allied health, or clinical research field Experience working in
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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