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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 days ago
inhibitors or CRISPR technology, accessing proteomic results from immunospheroid cultures. The work to be carried out by the PhD fellow includes the curation and management of a blinded clinical database
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the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image
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Requirements: PhD in geophysics, geology, geomatics, geodesy, geomatics, electrical engineering, computer science, natural hazards, or a related field Demonstrated skills in remote sensing, image processing
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engineering, and drug delivery approaches for improving human health in a sustainable manner. Currently, three directions are being explored: (1) engineering probiotics to secrete biologics such as nanobodies
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hospital intensive care unit. The post holder will have primary responsibility for the development and evaluation of the system, and of the data processing and image display software. The post holder will
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appoint you to this position. Admission to the PhD programme For employment in the PhD position, you must be qualified for admission to the PhD programme at the Faculty of Science and Technology and
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inspection, develop a database of raw and processed thermographic images of different defects - geometries on composites, test of thermographic image processing tools and techniques (all applicable
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they are developing Required Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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science/physics/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision A solid and