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simulations, microwave power deposition, tissue perfusion, and bioheat transfer. Perform mesh-convergence, sensitivity, uncertainty, and model-verification analyses. Compare computational predictions with
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research and clinical progress into various commercial applications, while integrating market validation, business-model development, strategic partnerships, IP and licensing strategy, regulatory
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. Requirements: 1. A PhD in computer science, electrical engineering, or related fields. 2. Research experience in deep learning model watermarking, media watermarking, or AI security. 3. Proficient in Python
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 10 hours ago
applied for, in accordance with the Background Checking Procedure and the National Higher Education Code to Prevent and Respond to Gender-Based Violence . Closing date: Sunday, 15 November, 11:55PM
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Christy Houston Foundation Drug Information Center including: responding to drug information requests, fact checking, and resource management. Participate in a teaching certificate program (if eligible
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datasets, remote sensing products, and reanalysis. • Integrate and compare observations, NWP model outputs, and nowcasting model products for hazard prediction workflows. • Develop and apply machine
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candidate will conduct model verification, sensitivity analysis, calibration, validation, performance evaluation, and troubleshooting. The position requires strong scientific programming and software
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mentorship from the principal investigator, you will conduct independent research to model adaptive oncogenesis and determine how age-related changes in the breast tissue microenvironment create selective
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% superannuation About the position The HIV PozQoL Partnerships Project is a pilot study to co-develop and evaluate the ‘PozQoL Partnerships model’; a patient care model and implementation protocols to
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AI with crystal plasticity finite element and phase-field simulations. Combine simulation and experimental data for model training, calibration and validation. Apply inverse design and optimisation to