Bioinformatics RA III or Scientist I (AI/ML - Assay Design)

Job Responsibilities:

• Develop scalable bioinformatics pipelines to process and analyze high-throughput PCR and NGS datasets
• Transform raw experimental data into structured datasets for AI/ML modeling
• Engineer biologically relevant features, including sequence composition, thermodynamics, and secondary structure
• Design, train, validate, and deploy machine learning and deep learning models for primer efficiency, specificity, and robustness
• Integrate sequence-derived features, thermodynamic calculations, and experimental outcomes into predictive models
• Build reproducible ML workflows supporting end-to-end assay design automation
• Continuously improve and retrain models using newly generated experimental data
• Develop AI-powered tools for primer design, assay optimization, and biological data interpretation
• Apply LLM-based methods for sequence annotation, workflow automation, and design recommendations
• Build reusable internal platforms that support AI-assisted assay development
• Collaborate with cross-functional research and development teams to improve diagnostic assay performance
• Document workflows, models, and analytical methods following scientific best practices

Skills:

• Strong background in bioinformatics, computational biology, and sequence analysis
• Proficiency in Python for scientific programming and data analysis
• Experience developing machine learning and deep learning models using PyTorch, TensorFlow, or scikit-learn
• Knowledge of PCR, NGS, primer design, and molecular biology workflows
• Experience with bioinformatics tools such as Primer3, BLAST, and Biopython
• Strong data analysis skills using Pandas, NumPy, and SciPy
• Experience building reproducible bioinformatics pipelines using Nextflow, Bash, or similar workflow tools
• Familiarity with Linux command-line environments and shared computational infrastructure
• Experience using Git for version control and collaborative software development
• Knowledge of AI-assisted development, LLMs, workflow automation, and sequence-based modeling is preferred
• Strong analytical, problem-solving, and communication skills

Education/Experience:

• 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
• Experience with bioinformatics, AI/ML, and computational biology workflows
• Background in assay development, genomic data analysis, or molecular diagnostics preferred