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Qualifications Experience with bioinformatics analyses of small RNA transcriptomes. Experience with next-generation sequencing (NGS) technologies and associated data analysis. Record of scholarly
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Qualifications Experience with bioinformatics analyses of small RNA transcriptomes. Experience with next-generation sequencing (NGS) technologies and associated data analysis. Record of scholarly
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cell culture, differentiation, characterization, and disease-relevant assays. Designs, implements, and operates bioinformatics pipelines using existing analytical tools for NGS applications that
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as scRNA-seq, scATAC-seq, NGS, WGS/WES, GWAS, etc. Apply statistical genetics analysis frameworks such as LDSC, p-HESS, eQTL, QTL-GWAS, Mendelian randomization, statistical colocalization, etc
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 14 hours ago
analysis, and phenotyping. Ultimately, the project aims to develop approaches for predicting and selecting stable polyploid lines, helping establish a new breeding strategy for more resilient and productive
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imaging and quantitative data analysis. Main tasks - Generate isogenic leukemia cell-line models carrying clinically relevant TP53 alterations using CRISPR/Cas-based genome editing. - Establish models
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, Micro-C, ChIP-seq, RNA-seq data from patient samples and myeloma cell lines. Preferred: experience with NGS analysis, R/Python, other computational languages, bioinformatic analysis. References
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pipelines using existing analytical tools for NGS applications that includes analysis of bulk and single cell genomic and transcriptomic datasets. Applies intellectual curiosity and a passion for data science
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-generation sequencing (NGS) data analysis Understanding of epigenome biology Solid programming skills in scripting and/or compiled languages Familiarity with Linux/Unix environment and compute clusters
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collaboratively in an interdisciplinary laboratory setting. Desired Qualifications: Experience with next-generation sequencing (NGS) data , microbiome composition analysis, or within-host genetic