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of geographic information systems, epidemiology, machine learning and public health information systems. The project aligns with recent developments at the HISP Centre at UiO, which is expanding its long-standing
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remodeling. We employ advanced computational and theoretical techniques, such as large scale flow network simulations, machine learning, and methods from topological data analysis, to a broad set of problems
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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integrating them with microfluidics as a standalone device. This is a great opportunity to learn new skills, contribute to assay development, and intellectually contribute to projects within a collaborative
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assimilation, and machine learning frameworks. Expertise in modeling geophysical systems. Strong proficiency in machine learning libraries such as PyTorch. Proficiency in writing clean, efficient, and well
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, i.e., machine learning models explicitly constrained by physical laws (e.g., conservation of mass, momentum, or energy) or designed to integrate physics-based models and data-driven learning
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will focus on the work package 'Learning, economic policy and business strategy in neutral countries'. During the First World War, the economies and companies of neutral countries adjacent to the Central
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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to build up a researcher profile and competence that qualifies the person to apply for a position as associate professor. The postdoctoral researcher will focus on the work package 'Learning, economic policy
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reputed refereed journals and presenting at conferences. Technical expertise in programming (e.g. python) and experience with high-performance computing are highly desirable. Experience in machine learning