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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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heterogeneous multi-omics datasets. Integrative Data Analysis: Perform and lead analysis of large-scale multi-omics datasets, including RNA/DNA sequencing, methylation, and metabolomics. Method Development
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& AI hardware or brain-inspired AI algorithm development, spatial analysis of multi-omics data. We are particularly interested in applicants with a demonstrated track record of translating discoveries
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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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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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on developing the next generation of approaches for analyzing spatiotemporal data arising from sports matches (e.g., tactcal analyses, player/team evaluation, …). See https://dtai.cs.kuleuven.be/sports 4) 1-2
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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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. You can continue your career journey with us! The Slomka Laboratory focuses on developing innovative methods for fully automated analysis of nuclear cardiology data using novel algorithms and machine
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. You can continue your career journey with us! The Slomka Laboratory focuses on developing innovative methods for fully automated analysis of nuclear cardiology data using novel algorithms and machine
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tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development of user