Baylor Genetics-posted 2 days ago
Full-time • Senior
Remote • Houston, TX
251-500 employees

We are seeking a highly experienced and innovative Senior NGS Algorithm Developer to lead the design and optimization of computational pipelines for next-generation sequencing (NGS) data. This role focuses on the detection and interpretation of a wide range of genomic features, including small variants (SNVs/Indels), copy number variants (CNVs), short tandem repeats (STRs), methylation patterns, and variants in homologous and homopolymer regions. Expertise in cancer genomics, somatic variant detection, and secondary analysis of NGS data required. 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. This role may be performed remotely, hybrid, or onsite, based on candidate preference and business needs.

  • Design and implement robust, scalable algorithms for: small variants, CNV detection, STR genotyping, methylation analysis, variant resolution in homologous and homopolymer regions, PGx variant calling, including hybrid alleles and copy number estimation in complex loci (e.g., CYP2D6, TPMT, UGT1A1)
  • Develop and apply algorithms for somatic SNV/Indel calling, CNV and structural variant detection, as well as methylation, alternative splicing, and fusion analysis in cancer transcriptomes
  • Integrate phasing and allele-specific analysis for small variants and methylation
  • Collaborate with assay scientists and software engineers to translate biological requirements into computational solutions
  • Benchmark algorithm performance using public and internal truth sets
  • Maintain reproducible workflows using tools like Nextflow, and Docker
  • Contribute to publications, presentations, and intellectual property development
  • Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related discipline
  • Minimum 5 years of experience in NGS algorithm development
  • Proficiency in Python, R, C++, and workflow orchestration tools
  • Deep understanding of: Read alignment and variant calling (e.g., BWA-MEM, minimap2, GATK, DeepVariant), CNV modeling, STR detection tools and methylation callers, Homologous region analysis and control gene normalization, PGx variant interpretation and allele resolution
  • Experience with long-read technologies (ONT, PacBio) and signal-level data
  • Strong analytical, problem-solving, and communication skills
  • Experience with machine learning models for variant classification
  • Knowledge of clinical genomics and regulatory standards
  • Familiarity with pharmacogenomic databases (e.g., PharmGKB, CPIC)
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