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longitudinal cohorts, SATSA and Betula, integrating established dementia biomarkers with inflammatory, metabolic, and genetic data using advanced statistical modeling and data-driven methods. The doctoral
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits
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)statistics, (applied) mathematics, computer science, or a related field; candidates from other fields with strong programming/coding skills (see below) are also encouraged to apply. Proficient in at least one
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equivalent, in bioinformatics, data science, computer science, computational biology, statistics, public health, biomedical engineering, applied mathematics, physics, or another quantitative field of relevance
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R and/or Python, with experience in data integration and statistical analysis. Exposure to RNA therapeutics or functional genomics approaches is an advantage. Strong interest in interdisciplinary
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independently. Merits: Education or training in computer vision, machine learning, deep learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics