Scientist I

Job Description

Job Summary:

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

Duties and 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.

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, TensorFlow, or scikit-learn.

Preferred Qualifications:

• 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.

Technical Skills:

• Programming: Python (required), R, Git.
• Bioinformatics Tools: Primer3, BLAST, Biopython.
• Data & Engineering: Pandas, NumPy, SciPy, pipeline development.
• Machine Learning: PyTorch, TensorFlow, scikit-learn, XGBoost, LightGBM.
• AI/Automation: LLMs, workflow automation tools, AI-assisted development.
• Operating Systems: Linux command-line environments, Linux-based servers, shared computational infrastructure.