Principal Bioinformatician

Hologic•San Diego, CA

18h•Onsite

About The Position

We are seeking an innovative and highly experienced Principal Scientist in Bioinformatics to lead the design, development, and optimization of advanced PCR-based multiplex assays using cutting-edge computational and AI-driven approaches. This role will combine deep expertise in molecular assay design, bioinformatics algorithms, and machine learning/AI to enable next-generation diagnostic and research solutions. The ideal candidate will be a scientific leader in shaping the future of AI-driven molecular diagnostics, applied with your a proven track record of translating biological insights into scalable computational tools and robust assay designs, particularly in molecular diagnostics, such as multiplex PCR and qPCR. This is an onsite role in San Diego, CA.

Requirements

Ph.D. in Bioinformatics, Computational Biology, Genomics, Molecular Biology, or a related field.
8+ years of relevant experience (industry preferred), including leadership responsibility.
Deep expertise in: Machine Learning / AI related to molecular diagnostics
PCR primer/probe design, including multiplex assay design principles
Bioinformatics tools (e.g., BLAST, alignment algorithms, sequence databases)
Programming (e.g., Python, R, or similar)
Demonstrated experience applying machine learning or AI to biological or genomic data.

Nice To Haves

Experience with high-plex assays, digital PCR, qPCR, or NGS-based diagnostics.
Knowledge of thermodynamics of nucleic acid interactions and assay chemistry.
Familiarity with cloud computing and scalable pipelines (e.g., AWS, Azure, GCP).
Experience in regulated environments (e.g., CLIA, FDA, IVDD/IVDR).
Publication record or patents in assay development, bioinformatics, or applied AI.

Responsibilities

Lead the strategy and execution of bioinformatics efforts for multiplex PCR assay design and optimization.
Serve as a subject matter expert in AI driven assay design, including target selection, primer/probe design, specificity analysis, cross-reactivity minimization, and multiplex compatibility.
Drive innovation through the integration of AI/ML models to improve assay performance, design efficiency, and predictive accuracy.
Mentor and guide cross-functional scientists in bioinformatics, molecular biology, and data science.
Develop and implement computational pipelines for high-quality primer and probe design for complex multiplex assays.
Optimize assays for sensitivity, specificity, and robustness across diverse sample types and targets.
Conduct in silico validation including thermodynamic modeling, sequence alignment, and off-target prediction.
Collaborate with wet-lab teams to iterate on assay performance using experimental feedback.
Design and deploy AI/ML models to: Predict primer/probe efficiency and multiplex interactions, Optimize assay conditions and configurations, Analyze amplification data and improve signal interpretation, Apply deep learning or probabilistic modeling approaches to sequence and assay design problems.
Stay current with emerging AI techniques and apply them to molecular diagnostics challenges.
Build and maintain scalable pipelines for genomic data processing, annotation, and analysis.
Integrate public and proprietary datasets to inform assay design and validation.
Develop software tools to automate and standardize assay workflows.
Partner with R&D, computational biology, software engineering, and product teams to deliver end-to-end solutions.
Communicate complex computational concepts to non-technical stakeholders.
Support regulatory and clinical teams with analytical validation data.