Bioinformatics Scientist

333 Lakeside Drive, CA, US • Posted 2 hours ago • Updated 2 hours ago
Contract W2
On-site
$75/hr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • FOCUS
  • Data Quality
  • Screening
  • Mapping
  • Management
  • IaaS
  • Bioinformatics
  • Biology
  • Computer Science
  • Assembly
  • Python
  • Bash
  • Linux
  • HPC
  • LSF
  • Amazon Web Services
  • Cloud Computing
  • Software Engineering
  • Git
  • Version Control
  • Testing
  • Documentation
  • Workflow
  • Publications
  • RNA
  • Web Browsers
  • Visualization
  • AWS Batch
  • Amazon S3
  • Data Management
  • Communication
  • Collaboration
  • Genomics
  • Research
  • Innovation

Summary

Job description:

Bioinformatics Engineer T2T Genome Assembly (Non-Model Organisms)

Location: Foster City CA/Hybrid (as applicable)
Duration: 12-Month Contract

We are seeking a highly skilled Bioinformatics Engineer to support the development of Telomere-to-Telomere (T2T) reference genomes for non-model organisms. This role will focus on building, optimizing, and operating long-read genome assembly and curation pipelines using PacBio HiFi and/or Oxford Nanopore sequencing data, while collaborating closely with wet-lab and computational biology teams.

Key Responsibilities

  • Design and execute genome assembly strategies for non-model organisms, including data quality assessment, genome profiling, contamination screening, and sequencing recommendations.
  • Perform long-read genome assemblies using tools such as Hifiasm, Verkko, Flye, and Canu, driving assemblies toward chromosome-scale and T2T-quality results.
  • Resolve haplotypes and complex genome structures, including highly heterozygous and polyploid genomes, utilizing approaches such as trio binning and Hi-C/Strand-seq-assisted phasing.
  • Scaffold and curate assemblies using long-range genomic data, including Hi-C, Omni-C, Strand-seq, and optical maps.
  • Identify and correct assembly errors, close gaps where feasible, and document curation decisions.
  • Evaluate assembly quality using tools such as Merqury, BUSCO, QUAST, k-mer analyses, and read-mapping approaches.
  • Develop and maintain scalable bioinformatics workflows using Nextflow, Snakemake, or WDL.
  • Deploy and manage workflows across on-premises HPC environments and AWS cloud infrastructure.
  • Generate technical reports, release documentation, and data packages for internal and external stakeholders.

Required Qualifications

  • PhD in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field.
  • Hands-on experience with de novo genome assembly using long-read sequencing technologies (PacBio HiFi and/or Oxford Nanopore).
  • Strong expertise with assembly tools such as Hifiasm, Verkko, Flye, Canu, or similar platforms.
  • Experience assessing assembly quality, troubleshooting assembly issues, and improving genome completeness.
  • Strong programming skills in Python and/or Bash within Linux environments.
  • Experience with workflow development using Nextflow, Snakemake, or WDL.
  • Experience running large-scale genomics workloads on HPC environments (Slurm, LSF, or similar).
  • Familiarity with AWS cloud services and scalable genomics computing environments.
  • Strong software engineering practices, including Git version control, testing, and documentation.

Preferred Qualifications

  • Experience working with non-model organisms and complex genomes.
  • Demonstrated success delivering chromosome-scale or T2T genome assemblies.
  • Knowledge of repeat annotation, genome annotation, and evidence-driven gene annotation workflows.
  • Experience with haplotype-resolved assemblies and advanced genome curation.
  • Publications, preprints, reference genome releases, or contributions to community genomic resources.

Nice to Have

  • RNA-Seq integration and genome annotation experience.
  • Genome browser track generation and visualization experience.
  • AWS Batch, HealthOmics, and S3 data management expertise.
  • Excellent communication skills and ability to collaborate across multidisciplinary teams.

This is an exciting opportunity to contribute to cutting-edge genomics research and help deliver high-quality reference genomes that support scientific discovery and innovation.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91082005
  • Position Id: 2026-25945/141779
  • Posted 2 hours ago
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