Computational biologist

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?

Your day is in a dry lab, at a computer. You take RNA-seq, single-cell RNA-seq, ChIP-seq, spatial transcriptomics and whole-genome sequencing files, run quality control with FastQC, and clean them. Then you combine genomics, transcriptomics, proteomics and metabolomics data to look for differential expression, disease pathways and drug targets. You run protein-ligand binding calculations and work with AlphaFold structures, and you keep Snakemake or Nextflow pipelines running on a SLURM Linux HPC cluster or on AWS Batch and Google Cloud Life Sciences.

Your daily tools are Python, R, Bioconductor, DESeq2, Seurat, scanpy, Pandas, NumPy, Scikit-learn, Biopython, BWA, Bowtie2, Samtools, GATK, Bedtools, FastQC, Docker/Singularity, AWS S3/EC2 and Git. You explain the statistics and biology to wet-lab scientists, chemists and medical directors. About 15% to 20% of the time is new target discovery and machine learning modeling, 50% to 60% is data cleaning, metadata reformatting and pipeline debugging, and 20% to 25% is meetings, slides, grant and paper writing and code documentation. It is a 40-hour week, with no shift work and no routine night shifts, except evening and weekend pipeline monitoring during urgent submission milestones or long compute runs.

Where does this lead?