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from diffusion tensor imaging of the heart along with all parameters determining the measurement process itself. Job description The position to fill concerns advanced data synthesis (both via machine
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. Dagmar Iber, which uses advanced imaging and computational tools to develop data-driven, mechanistic models of biological systems. Located in Basel, the Department of Biosystems Science and Engineering (D
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image processing techniques and modern machine learning approaches to extract meaningful quantitative information from complex biological images. The successful candidate will contribute to projects
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. Interactions with the recently created Dubochet Center for Imaging are highly encouraged. One or two of the following research topics should be covered in the application: Machine Learning and AI-inspired
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machines (data movers, data pipelines, storage management). Scouting for new commercial and open-source software tools. Develop image analysis-based quality control tools for microscopes. Profile We
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samples, sectioning, immunostaining Acquire a series of confocal microscopy images Quantify images using pre-defined algorithms Prepare GLP compliant reports Your profile Biologielaborant/in (or equivalent
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, data science, and industrial applications. As part of this position, you will: Develop and implement advanced Machine Learning models to analyze large datasets, including image and time-series data
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, computer engineering and/or computer science towards producing relevant and impactful health-monitoring mobile/wearable solutions, then please apply. The research will be highly collaborative; you should be
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responsible for ensuring the smooth operation of the IT infrastructure and services at NEXUS. Your responsibilities are: Core Responsibilities: Setup and manage virtual machines within ETH Zurich’s
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velocity changes at selected locations with the introduction of unsupervised machine learning and study the interaction of mass balance changes (crustal stress changes) and geohazards such as rain-induced