Scientist, Data Scientist

Bioinformatics Scientist (AI/ML – Assay Design)

We are seeking an innovative Bioinformatics Scientist with expertise in AI/ML to build next-generation, high-throughput primer design systems for ***'s 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.

Key Responsibilities

• Experimental Data Analysis
• 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)
• Machine Learning Development
• 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
• Model Iteration & Optimization
• Continuously refine models using newly generated experimental data
• Implement frameworks for iterative learning, model retraining, and benchmarking
• AI-Driven Applications
• 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

Required Qualifications

• Education:
  
  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
• Bioinformatics:
  Strong foundation in sequence analysis, primer design, and computational biology workflows
• Programming & Data Analysis:
  Proficiency in Python, with experience in statistical analysis and experimental data interpretation
• Machine Learning:
  Hands-on experience developing ML or deep learning models using frameworks such as PyTorch, Tensor Flow, or scikit-learn

Why This Role Is Exciting

You will apply AI/ML to molecular biology to design better assays for women's health and infectious disease detection.