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learning models for digital phenotyping and genomics Work with multimodal datasets (images, 3D data, motion, genomics) Implement models in Python (e.g. PyTorch) using high-performance computing
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group has performed the largest multi-omics characterization of CRC to date, encompassing WGS and RNA-seq of 1,063 patients Building on this foundation, sub-cellular spatial transcriptomics (Stereo-seq V1
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for and perform integration of modalities with varying dynamic range, sparseness and non-linear behavior, (ii) establish discovery methods for multicellular immune niches, (iii) follow B-cell clonal
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. Academic and Research Excellence: Demonstrated high-quality academic performance, including strong grades and relevant degree projects. Prior research experience in computational biology, functional genomics
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of polyploid genome evolution across contrasting timescales. The student will receive interdisciplinary training in bioinformatics, evolutionary genomics, and high-performance computing within the DDLS data
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support for performing the doctoral project. About the PhD project: CRITICAL AI – Comprehensive Research on InfecTIons Across the Lifespan using AI The aim of the doctoral project is to develop robust and
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of LNPs under various storage conditions, the aim is to develop formulations with both high performance and improved stability. The work includes the design and systematic screening of LNP formulations