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We are seeking an innovative Bioinformatics Scientist with expertise in AI/ML to build next-generation, high-throughput primer design systems for our diagnostic platforms. In this role, you will combine molecular biology, machine learning, and data engineering to develop intelligent pipelines that translate experimental data into improved assay performance. You will build models that learn from large-scale PCR and sequencing datasets, enabling data-driven optimization of assay design. This role is ideal for someone excited about applying modern ML and AI techniques—including deep learning and emerging language model approaches—to real-world diagnostic challenges.
Job Responsibility
Develop scalable pipelines to process and analyze high-throughput PCR and NGS datasets
Transform raw experimental outputs into structured datasets for modeling
Engineer biologically meaningful features (e.g., sequence composition, thermodynamics, secondary structure)
Design, train, and deploy models to predict primer efficiency, specificity, and robustness
Integrate sequence-derived features, thermodynamic calculations, and experimental outcomes
Build reproducible ML workflows that support end-to-end assay design automation
Continuously refine models using newly generated experimental data
Implement frameworks for iterative learning, model retraining, and benchmarking
Develop AI-powered tools to support primer design, assay optimization, and data interpretation
Apply LLM-based methods for sequence annotation, workflow automation, and design recommendations
Contribute to reusable internal platforms enabling AI-assisted assay development at scale
Requirements
Ph.D. (0–2 years), M.S. (2–4 years), or B.S. (3–5+ years) in Bioinformatics, Computational Biology, Data Science, Molecular Biology, or a related field
Strong foundation in sequence analysis, primer design, and computational biology workflows
Proficiency in Python, with experience in statistical analysis and experimental data interpretation
Hands-on experience developing ML or deep learning models using frameworks such as PyTorch, TensorFlow, or scikit-learn
Nice to have
Experience with sequence-based modeling or genomic data analysis
Experience developing or maintaining reproducible bioinformatics workflows (e.g., Nextflow, Bash)
Experience working in Linux command-line and shared server environments
Experience using Git (e.g., pull requests, code review, issue tracking)
Understanding of PCR chemistry and assay design principles