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omics data analysis. A high level of self-motivation and independence, good problem-solving skills, and the ability to work collaboratively in an interdisciplinary research environment. The ability
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the MIDA – Methods for Image Data Analysis – research group at the Department of Information Technology, and will be conducted alongside other researchers at the Centre for Image Analysis who develop
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data with computational modeling Programming skills in Python, R, or another relevant language. Interest in machine learning, statistical modeling, structural bioinformatics, or analysis of large-scale
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(e.g., Snakemake, Nextflow) and reproducible data processing pipelines. Knowledge of transcriptomics and alternative splicing analysis, including isoform-level quantification tools. Programming skills in
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, or a related field, who enjoys interdisciplinary work spanning wet-lab experimentation and computational data analysis. In addition to the aforementioned requirements for the position: A Master’s
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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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experience in population genomic modeling (e.g., using SLiM), analysis of structral variants from long‑read data, population genomic analysis of whole‑genome re-sequencing data are a merit — these techniques
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precision medicine and diagnostics covers data integration, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and
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fecal shotgun data from 500 children followed from birth to three years of age to investigate how environmental, clinical and lifestyle exposures shape microbial community development. The student will be