Summary

NIH-funded Garcia Lab at Baylor College of Medicine develops computational methods to discover male-infertility genes and contraceptive targets using Oxford Nanopore long-read sequencing, machine learning for gene-disease and protein–protein interaction prediction, and rapid knockout mouse validation. The Bioinformatics Programmer I will refine and operate production pipelines, build ML models, analyze large cohorts, and deliver publication-quality results in a fast, collaborative environment within the Texas Medical Center.

Job Duties

• Builds, refines, and operates production pipelines for Oxford Nanopore long-read WGS, variant/SV calling, transposable element, and downstream gene-disease and in-silico PPI prediction.
• Develops, trains, and evaluates machine-learning models in PyTorch for gene prioritization and PPI prediction.
• Implements reproducible experiments and benchmarks.
• Performs large-scale QC, statistical analysis, and visualization; generate publication-ready figures, tables, and dashboards for manuscripts and conference presentations.
• Extends and hardens lab software: write clean, tested Python; package tools, version with Git, and document for internal and external users.
• Integrates and benchmarks third-party bioinformatics tools.
• Optimizes compute (HPC/cloud), memory, and I/O; profile and remove bottlenecks.
• Practices vibe coding: rapid prototyping, tight feedback loops, clear naming, and code readability that improves team velocity.
• Leads and co-author methods and application manuscripts.
• Prepares datasets, code, and supplementals for public release.
• Partners with wet-lab and external collaborators; plan milestones, track deliverables, and report progress to the PI.
• Performs related-duties as assigned to meet project objectives.

Minimum Qualifications

• Bachelor's degree in Computer Science, Biological Science, or a related field.
• No experience required.

Preferred Qualifications

• Master’s degree in a related field.