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development, high-throughput data analysis, and working with large population-based cohorts and clinical biobanks. The student will learn how to scientifically assess the study quality, perform appropriate
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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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Bioinformatician: Data Science lead The Department of Biochemistry and Biophysics. SciLifeLab (SciLifeLab ) is a national center for molecular biosciences with focus on health and environmental
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microscopy, image analysis: Development of microscopes, fluidics, and data analysis pipelines used to acquire and quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering
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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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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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, 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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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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of pancreatic cancer. This group is led by Associate Senior Lecturer Dr. Qiaoli Wang, as part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS). Group members will be enrolled