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Senior Bioinformatics Scientist / ML Engineer - PhD Only

Genenet
Cambridge
1 month ago
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Senior Bioinformatics Scientist / ML Engineer - PhD OnlySenior Bioinformatics Scientist / ML Engineer - PhD Only

2 weeks ago Be among the first 25 applicants

We are seeking an experienced and forward-thinkingSenior Bioinformatics Scientist / ML Engineerto 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

Pays:

  • £51,736.00-£60,088.00 per year
  • Company pension
  • Employee stock purchase plan
  • Free parking
  • On-site parking

Schedule:

  • Flexitime
  • United Kingdom (required)

Work Location:

  • On-site (preferred) or Hybrid remote in Cambridge CB2 0AW

Reference ID: SeniorbioinfoML

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionResearch, Analyst, and Information Technology

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