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Organization U.S. Department of Defense (DOD) Reference Code DEVCOM-SC-2026-0003 How to Apply Click on Apply at the bottom of the opportunity to start your application. Description The Department
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
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31, 2026. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The position is placed in the Digital Signal Processing and Image Analysis group (DSB
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to: Contribute to development and deployment of particle imaging systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis
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, working closely with other project participants on field measurements, laboratory work and model development. The candidate will be expected to: Contribute to development and deployment of particle imaging
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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and develop the corresponding biasing network.; • Fabricate and assemble a proof-of-concept prototype on a glass substrate.; • Experimentally characterize the electromagnetic performance
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demonstration of a prototype in a laboratory environment, as well as integration into real use cases ; - Writing project documentation and scientific publications. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND
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radiation, radioactive substances and non-ionising radiation to produce diagnostic quality images of the human body, facilitating the diagnosis and treatment of patients (Allied Health Professions Act 2011
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achieve outstanding performances in recognizing objects in an image, inferring their relationships, and generating image descriptions in natural languages. They're ideal for tasks like image captioning