Bioinformatics Scientist, NGS Data Analysis

We are looking for a talented Ph.D. level Bioinformatics Scientist specialized in NGS data analysis, with a deep expertise in single-cell technologies and multiomics approaches. This scientist will play a key role in developing and implementing computational pipelines and tools for analyzing complex NGS datasets. As a member of our Research Bioinformatics team, you will work at the intersection of computational biology, machine learning, and biotechnology to leverage innovative algorithms and analytical methods to support collaborative research initiatives and drive scientific discoveries and biotech innovations.

Primary Responsibilities:

• Develop Computational Pipelines & Tools for Single-Cell and Spatial Transcriptomics Analysis: Build, optimize, and deploy scalable and reproducible pipelines for the analysis of single-cell NGS datasets, including scRNA-seq, spatial transcriptomics, and single-cell methylation sequencing, ensuring scalability, high-quality results and novel biological insights.
• Establish Analytical Capabilities for Multiomics Integration: Develop and deploy tools for the integration and analysis of diverse omics data types—such as genomics, transcriptomics, epigenomics (including DNA/RNA modifications, chromatin accessibility, and 3D genome architecture)—to support a holistic understanding of complex biological systems and drive research hypothesis generation.
• Leverage Machine Learning for NGS Data Interpretation: Apply and develop state-of-the-art machine learning algorithms to enhance data interpretation, increase analytical throughput, and uncover novel biological patterns in large-scale NGS datasets.
• Collaborate Cross-Functionally to Support NGS-Based Research Projects: Work closely with wet-lab scientists, project leads, and other computational team members to analyze and interpret experimental data, provide expert bioinformatics support, and contribute to research planning and strategy.
• Publication & Thought Leadership: Contribute to the publication of results in peer-reviewed journals and conferences. Present findings and methodologies to both internal and external stakeholders.

Required Qualifications and Experience:

• Education: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field.
• Technical Expertise: Proven experience in NGS data analysis, experience in single-cell sequencing technologies (e.g., scRNA-seq, single-cell methylation sequencing) and data analysis is highly desired. Strong background in computational pipeline development using languages such as Python, R, or similar. Experience with multiomics integration, spatial transcriptomics, and related advanced sequencing technologies is highly desirable. Solid understanding of machine learning techniques, particularly in the context of biological data analysis (e.g., clustering, dimensionality reduction, predictive modeling). Experience with software development practices (e.g., version control, testing, documentation) is preferred.
• Analytical Skills: Extensive experience with bioinformatics tools, software packages, and databases used for genomic analysis. Ability to handle large-scale, high-dimensional datasets and apply statistical methods to extract meaningful insights. Excellent collaboration skills, with the ability to work effectively in multidisciplinary teams. Strong written and verbal communication skills to present complex analytical concepts to both technical and non-technical audiences.

New England Biolabs is committed to fostering a diverse and inclusive community. As an Equal Employment Opportunity employer, New England Biolabs considers applicants for employment without regard to and does not discriminate on the basis of any category protected under applicable federal, state, or local laws and regulations.