John Palmer
$ whoami
Genomics software built for real-world decisions
I am a genomics software developer and bioinformatician who turns difficult scientific analyses into reliable production systems. I work across Python, Nextflow, databases, HPC, and AWS—with independent validation and operational adoption treated as part of the engineering, not as afterthoughts.
role Genomics Software Developer
location Toronto, Ontario, Canada
focus Production scientific software
method Build → validate → operateSelected systems
The strongest examples of my work are systems that connect biological analysis to dependable engineering and documented evidence.
01 / VALIDATED GENOMICS
Influenza surveillance
A production mutation-analysis platform spanning Python and Nextflow, with reference-aware annotation, configurable watchlists, structured reporting, and independent validation across every influenza segment.
Role: Sole architect and principal developer, alongside leadership and contributions in shared upstream workflows.
02 / SECURE CLOUD
Sequence submission on AWS
A serverless service for partner-to-laboratory sequence transfer with separate machine and browser identity paths, immutable uploads, tenant isolation, confirm-before-expiry lifecycle controls, and permanent audit records.
Role: Sole architect and developer within a shared genomics cloud platform.
03 / WORKFLOW OPERATIONS
Automation and validation
An operational layer around pathogen-genomics pipelines: formal validation, dependency-aware orchestration, result aggregation, database integration, and downstream chaining on shared HPC infrastructure.
Role: Led the influenza transition and contributed across shared public health workflow repositories.
Evidence, not decoration
0.9915 all-SNV F1 across 192 samples × 8 segments
100% subtype and clade accuracy in stated validation cohorts
1,184 segment sequences in consensus-accuracy validation
Metrics are reported with their original scope. I use independent ground truths, predefined acceptance criteria, and discrepancy analysis to understand why a system succeeds or fails—not only whether a summary score looks good.
How I work
Production first
Scientific code should be versioned, observable, recoverable, and usable by the people who depend on it.
Validation is engineering
I design orthogonal tests, trace anomalies to root causes, and turn the findings into production fixes.
Boundaries matter
Identity, tenancy, failure modes, data ownership, and individual contributions should be explicit in both architecture and documentation.
Personal repositories
pyslurm
A typed Python interface for submitting and monitoring SLURM job arrays through Meta’s submitit.
agent-skills
Reusable agent skills for Nextflow, Python data work, visualization, and interactive dashboards.
Technical range
Python · Nextflow DSL2 · Bash · SQL · R · TypeScript · SLURM · Apptainer · Docker · PostgreSQL · SQLAlchemy · FastAPI · AWS CDK · S3 · Lambda · SQS · EventBridge · ECS Fargate · GitHub Actions