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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under
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School. Responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical
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and Correction of Industrial Design Flaws – Towards Fail-Safe Industries) is a Business Finland funded research project with the objective to develop a new type of computer-aided design platform
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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Computer Vision algorithms. Experience using urban building stock modelling and urban digital twins What you will do: Design & Develop: Create data structures for detailed, spatialised construction component
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. This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design, and
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-source project used by the scattering community Exposure to advanced data analysis methods and practical algorithm implementation Opportunity to work closely with scientists and software developers at MAX
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in Summer 2026, for a term of 2 years with the possibility of an extension. The postdoc will join the ERC-Starting Grant project team on “Participatory Algorithmic Justice: A multi-sited ethnography to