Senior ML Scientist - Single-Cell Biology & Genomics

Senior ML Scientist - Single-Cell Biology & Genomics

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
Relation Therapeutics

At a Glance

  • Tasks: Develop ML approaches for single-cell and multiomic datasets to drive therapeutic strategies.
  • Company: Relation Therapeutics, a pioneering firm at the intersection of ML and biology.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Collaborative environment with dynamic teams and exciting projects.
  • Why this job: Make a real impact in healthcare by translating complex data into actionable insights.
  • Qualifications: Strong ML fundamentals and deep understanding of biological data required.

The predicted salary is between 63000 - 77000 Β£ per year.

Relation Therapeutics in London seeks a Senior Machine Learning Scientist who combines ML fundamentals with deep biological data understanding.

You will develop ML approaches for single-cell and multiomic datasets to uncover cellular responses and inform therapeutic strategy.

You'll work at the intersection of ML and biology, collaborating with wet-lab teams, translating questions into modelling problems, and communicating findings across disciplines in a matrixed environment.

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Senior ML Scientist - Single-Cell Biology & Genomics employer: Relation Therapeutics

Relation Therapeutics is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. With a strong emphasis on inclusivity and impactful results, employees are encouraged to grow through continuous learning and development opportunities. Located in a vibrant area, the company fosters a culture that values teamwork and communication, making it an ideal place for those passionate about advancing drug discovery.

Relation Therapeutics

Contact Details:

Relation Therapeutics Recruitment Team

We think you need these skills to ace Senior ML Scientist - Single-Cell Biology & Genomics

Machine Learning Fundamentals
Single-Cell Biology
Multiomic Datasets
Data Analysis
Collaboration with Wet-Lab Teams
Modelling Problem Translation
Interdisciplinary Communication