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Monash/Bayreuth Double PhD Degree Opportunity - Accelerating organic semiconductor discovery with generative AI, molecular dynamics and DFT Job No.: 698040 Location: Clayton (home) and Bayreuth
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PhD Scholarship opportunity: Applied Economics on Patient-Centred Evaluation of medical devices (PACE) Job No.: 689544 Location: Caulfield campus Centre for Health Economics, Monash University
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to be unconventional. I have projects available within the following research areas (at both Honours or PhD level): "Excitons and excitonic superfluidity in monolayer semiconductors" "Interplay of Dirac
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sustainable energy materials through their atomic architecture Imaging symmetry at the atomic scale Understanding how nanocrystals grow Tuning the perovskite structure, from semiconductor to superconductor
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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-procedures. Expected commencement: 2 November 2026 The Opportunity We are seeking a highly motivated PhD candidate to join a translational medical-device research project developing a next-generation, jet
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on expensive manual annotations. To improve cross-device and cross-task generalisation, enabling models trained on one dataset or device to adapt to others with minimal retraining. To improve detection and
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five‑year collaboration integrating materials growth, advanced microscopy and spectroscopy, nanoelectronic device fabrication, and machine‑learning‑accelerated modelling. As a member of my group, you
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representations Efficient AI deployment on edge devices Real-world AI systems for security, healthcare and smart environments The research will utilise anonymised industry datasets and be validated using
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, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects