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Field
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development can alter tissue mechanical properties and allow cancer cells to withstand compressive forces within a tumour environment. This PhD project aims to map keratin network architecture in epithelial
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footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity. Key Responsibilities: To perform pioneer research in exploring learning-based model compression and green
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synthesis (images, text, audio, video), and complex reasoning. Investigate model compression, quantization, and distillation for efficient deployment. High-Performance AI Infrastructure (Infra): Design and
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the conceptual and technical skills to develop online content. Techniques covered include image preparation, video and audio compression, navigation, HTML and CSS authoring using Adobe Dreamweaver and Google
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patient medical advice requests. Process provider orders for medical compression garments. Collaborate with New Patient Coordinator to review new patient referrals for appropriateness. This includes
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mammography including training in breast anatomy and physiology, positioning and compression, QA/QC techniques, and imaging of patients with breast implants and completed 25 mammography examinations under
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office equipment. X-ray generator, image detector, compression paddles. Working Conditions Needs to be able to successfully perform all required duties. Office/healthcare environment; some travel, weekend
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. To set up and analyze experiments and datasets under different conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in a form of
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, encryption/decryption and compression; use of microelectronics devices (including COTS); implementation, inference, verification and validation of algorithms** on processing hardware platforms for space
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; For remote sensing, design and validation of on-board processing functions/algorithms for payload data products, image processing and optical payload data compression; Related end-to-end performance assessment