Job Description

Position Overview:

We are seeking an experienced and forward-thinking

Senior Bioinformatics Scientist / ML Engineer

to join our dynamic team. The ideal candidate will have a strong foundation in bioinformatics and significant experience applying machine learning (ML) methods--particularly in computer vision and regression--to complex biological datasets. You will play a key role in advancing our genetic engineering and synthetic biology initiatives by building scalable analytical pipelines and uncovering actionable insights from biological data.

Key Responsibilities:

Lead the design, development, and implementation of advanced bioinformatics pipelines and analytical tools to support genetic circuit engineering and related R&D projects. Apply state-of-the-art machine learning techniques, including computer vision, regression models, and potentially deep learning, to biological datasets (e.g. genomic, transcriptomic, single-cell). Collaborate closely with molecular biologists, data scientists, and software engineers to integrate ML-driven insights into our synthetic biology platform. Evaluate, benchmark, and optimize ML models for predictive performance and biological interpretability. Keep current with cutting-edge developments in bioinformatics and ML, and translate emerging techniques into practical solutions. Provide technical mentorship to junior bioinformaticians or ML interns as needed. Communicate complex findings clearly to stakeholders and contribute to publications, technical reports, and potential patent applications.

Required Skills & Qualifications:

PhD in Bioinformatics, Computational Biology, Computer Science, or a related discipline. Minimum of 3 years of hands-on experience in bioinformatics, especially in the analysis of high-throughput sequencing or other large-scale biological data. Proficiency in machine learning, particularly in applying computer vision and regression approaches to biological problems. Strong coding skills in Python, with experience using bioinformatics and ML libraries (e.g. scikit-learn, pandas, NumPy, Biopython). Demonstrated ability to design robust, scalable data analysis pipelines and deliver biological insights. Excellent communication skills with both technical and non-technical audiences. Experience working in collaborative, multidisciplinary environments.

Preferred Qualifications:

Experience with synthetic biology or genetic circuit design. Familiarity with deep learning techniques and frameworks (e.g., TensorFlow, PyTorch). Experience deploying ML models in production environments, preferably in cloud-based systems. Strong publication record in bioinformatics, machine learning, or synthetic biology journals. Familiarity with version control, reproducible research practices, and collaborative coding tools.

What We Offer:

A rare opportunity to work at the intersection of synthetic biology, computational biology, and AI/ML. A collaborative, innovative, and mission-driven team culture. Opportunities for leadership, professional development, and real scientific impact. Competitive salary and comprehensive benefits package. Flexible hybrid working model - work from home or at the Milner Therapeutics Institute (CB2 0AW) in Cambridge, depending on your preference and project needs.
Job Type: Full-time

Pay: 51,736.00-60,088.00 per year

Benefits:

Company pension Employee stock purchase plan Free parking On-site parking
Schedule:

Flexitime
Work authorisation:

United Kingdom (required)
Work Location: Hybrid remote in Cambridge CB2 0AW

Reference ID: SeniorbioinfoML
Expected start date: 16/06/2025