Senior ML Scientist, Generative Biomedicine in London

Senior ML Scientist, Generative Biomedicine in London

London Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Develop generative and predictive models using machine learning and biological data.
  • Company: Join a pioneering TechBio company in London focused on advancing medicines.
  • Benefits: Competitive salary, access to advanced technology, and collaborative team environment.
  • Other info: Work in a dynamic team with access to cutting-edge resources and interdisciplinary expertise.
  • Why this job: Push the boundaries of generative modelling and make a real impact in biomedicine.
  • Qualifications: Strong background in machine learning and understanding of biological data.

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

Relation is a Tech Bio company advancing medicines using single-cell multi-omics and machine learning in London.

We seek a Machine Learning Scientist who blends ML fundamentals with deep biological data understanding to build generative and predictive models of cellular behaviour.

You will join a team with access to multi-omic data, advanced compute, and interdisciplinary expertise. Expect to push the boundaries of generative modelling in real-world systems.

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Senior ML Scientist, Generative Biomedicine in London employer: Relationrx

Relation is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. As a Senior ML Scientist, you will have access to cutting-edge technology and resources, alongside opportunities for professional growth and development within a supportive team environment. Join us to make a meaningful impact in the field of generative biomedicine while working with some of the brightest minds in the industry.

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Contact Details:

Relationrx Recruitment Team

We think you need these skills to ace Senior ML Scientist, Generative Biomedicine in London

Machine Learning Fundamentals
Deep Biological Data Understanding
Generative Modelling
Predictive Modelling
Single-Cell Multi-Omics
Data Analysis
Interdisciplinary Collaboration