Bioinformatics bootcamp

Pay in the destination countries

Monthly, in US dollars. Each country is an Imora admission package — open one for that route's fees, language requirement and deadline.

What does the day look like?

A 40-hour work week centers on computational data curation, pipeline deployment, and biological interpretation. Around 60% of the day is spent on data cleaning, pipeline execution, and debugging: managing Linux bash environments, workflow engines like Nextflow, Snakemake, and Cromwell, HPC clusters (SLURM, SGE), and cloud platforms (AWS Batch, GCP Life Sciences). It also involves handling massive FASTQ, BAM, CRAM, and VCF files, maintaining Docker and Singularity containers, and running FastQC and MultiQC checks. Another 20% goes toward scripting in Python (pandas, Biopython, scanpy, pysam) and R (Bioconductor, DESeq2, Seurat) for differential gene expression, scRNA-seq, or GWAS studies. The final 20% involves Git/GitHub documentation, reproducibility tracking, and presenting findings to wet-lab biologists and clinicians.

While newcomers often imagine discovering cures with AI or designing novel proteins within minutes, the daily reality involves hours of resolving broken container paths, fixing SLURM memory allocation crashes, and converting coordinate files from hg19 to hg38. The role follows standard office hours (09:00 to 17:00 or 10:00 to 18:00) with no routine night shifts, though multi-day NGS batch runs occasionally require weekend checks.

Where does this lead?