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Baylor Genetics seeks a Senior Scientist in NGS Algorithm Development to design, optimize, and implement computational methods for diverse genomic features and chromosomal abnormalities. You will guide pipelines, ensure robustness, and collaborate across assay development, bioinformatics, and partner teams.
The ideal candidate holds a Ph.D. in Bioinformatics or related field with 5+ years of hands-on NGS algorithm experience, including PGx variant calling and complex loci analysis; experience
We are seeking a highly experienced and innovative Senior Scientist in NGS Algorithm Development to lead the design, optimization, and implementation of computational algorithms for next-generation sequencing (NGS) data. This role focuses on detecting and interpreting a wide range of genomic features and chromosomal abnormalities, including trisomy, small variants, copy number variants, short tandem repeats, methylation patterns, and variants in homologous and homopolymer regions.
The Senior Scientist will also lead the design and optimization of targeted NGS panels for existing and new products and drive the development, validation, and integration of NGS algorithms and analysis pipelines. As a technical and project lead, this role ensures analytical accuracy, robustness, and scalability across products, supports technology transfer and pipeline updates, and collaborates cross-functionally with assay development, bioinformatics, and partner teams to provide technical guidance and inform strategic decisions.
The ideal candidate will hold a Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field, and have at least 5 years of hands-on experience in algorithm development for NGS applications. Experience in pharmacogenomics (PGx) variant calling, including complex loci such as CYP2D6, is strongly preferred.
Preferred experience with Linux/HPC, Docker containerization, Nextflow workflow development, GitHub-based software engineering, and Python/Groovy programming. Familiarity with cloud platforms and NGS data formats (FASTQ, BAM, VCF), along with CI/CD, workflow automation, troubleshooting, and developing reproducible bioinformatics pipelines.
Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.
Equal Opportunity Employer
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