Posted:1 day ago|
Platform:
Hybrid
Full Time
Masters related to Bioinformatics and Computational Biology
- Combine and analyze multi-omics datasets to find common biological signals and
actionable targets.
- Classify disease and immune subtypes from both bulk and single-cell data using
supervised and unsupervised machine learning methods.
- Organize public datasets, evaluate analytical tools, and standardize workflows for clarity
and reuse.
- Conduct quality control, normalization, subtype and signature predictions across various
sequencing platforms.
- Create and maintain complete analysis pipelines for new technologies such as spatial
transcriptomics
- Search large consortia or databases for comparative studies and hypothesis generation.
- Optimize resource use and job scheduling on Linux or HPC clusters; maintain version
control and documentation.
- Programming & Scripting: R, Python, UNIX shell
- Statistics & ML: Feature selection, clustering, predictive modeling, dimensionality reduction, survival analysis
- Bulk & Single-Cell Analytics: RNA-seq, WES/WGS, methylation, proteomics, RPPA,
scRNA-seq
- Workflow & Reproducibility: Workflow managers, such as Nextflow or Snakemake,
containers, Git
- Data Resources: Major public repositories like TCGA and GEO, and internal cohort data
management
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