Senior Bioinformatics Scientist (South San Francisco, CA)
You will collaborate with molecular biologists, product teams, and manufacturing engineers to refine client’s core synthetic biology platform, troubleshoot assembly challenges , and improve DNA synthesis efficiency . This position emphasizes predictive modeling, algorithm development, and data-driven approaches to enhance synthetic biology workflows.
Key Responsibilities
Synthetic Biology & DNA Assembly
- Develop bioinformatics methods supporting DNA assembly strategies and synthetic biology workflows .
- Apply machine learning and predictive modeling to improve DNA assembly success rates and optimize synthesis parameters.
- Collaborate with wet-lab scientists to analyze and troubleshoot molecular biology processes.
- Develop bioinformatics approaches for diagnosing and resolving complex DNA synthesis and assembly issues.
- Build and maintain NGS analysis pipelines (e.g., Nextflow) to support quality control and performance tracking of synthetic biology products.
- Leverage Oxford Nanopore Technologies (ONT), Illumina, or PacBio sequencing to analyze and optimize synthesis workflows.
- Develop predictive models to identify challenging sequences and recommend optimizations to improve synthesis efficiency.
- Ensure pipeline accuracy, reproducibility, and scalability in research environments.
- Apply advanced statistical and machine learning methods to evaluate improvements in synthetic biology product iterations .
- Use Python, R, and visualization tools to generate actionable insights and present findings to stakeholders.
- Design and implement novel bioinformatics algorithms for sequence analysis and synthetic biology applications .
- Partner with R&D, manufacturing, and product development teams to troubleshoot assay issues and implement data-driven solutions .
- Support the broader Bioinformatics team by integrating synthetic biology workflows with existing genomic data processing pipelines.
- Assist with customer-facing analyses related to synthetic biology assay performance.
- Educational Background & Experience:
- Bachelor’s/Master’s degree with 6–8 years of industry experience , or a Ph.D. with 3+ years of industry experience in Bioinformatics, Molecular Biology, Biochemistry, Genetics, Genomics, Computational Biology, or a related field .
- Bioinformatics & NGS Expertise:
- Experience with ONT, Illumina, or PacBio sequencing technologies .
- Proficiency in workflow management tools (Nextflow, Snakemake).
- Hands-on experience designing predictive models for sequence design & synthetic biology applications .
- Technical Skills:
- Expertise in Python (Pandas, NumPy, SciPy) and visualization libraries (Matplotlib, Seaborn, Plotly).
- Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch) applied to biological sequence data.
- Familiarity with R, SQL, or other statistical tools .
- Molecular Biology & Synthetic Biology Knowledge:
- Understanding of DNA assembly, cloning techniques, and molecular biology workflows .
- Ability to interpret experimental data and provide feedback on laboratory procedures.
- Experience developing design algorithms for synthetic biology applications.
- Familiarity with deep learning approaches for biological sequence analysis.
- Exposure to high-throughput experimental design and laboratory automation.
- Hands-on experience with gene synthesis and synthetic biology assay development .
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