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Data Scientist / Comp Biologist

Robert Walters
Posted a day ago, valid for a month
Location

Cambridge, Cambridgeshire CB2 8AG, England

Salary

£75,000 per annum

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • I am recruiting for a highly skilled and motivated Data Scientist / Computational Biologist to join an exciting start up team.
  • The ideal candidate will have a PhD in Computational Biology, Bioinformatics, Data Science, or a related field with a strong background in biological data analysis and machine learning.
  • This role requires hands-on experience with next-generation sequencing (NGS) technologies and the ability to work collaboratively in a multidisciplinary environment.
  • Key responsibilities include implementing and optimizing machine learning models, working with large-scale biological datasets, and presenting complex biological information intuitively.
  • The position offers a salary of up to £75,000 per annum and comes with a wealth of benefits.

I am recruiting for a highly skilled and motivated Data Scientist / Computational Biologist to join an exciting start up team.

The ideal candidate will have a strong background in biological data analysis, machine learning, and computational biology, with a focus on protein language models and next-generation sequencing (NGS). This role requires an individual who can hit the ground running and contribute to their multidisciplinary research efforts.

Key Responsibilities:

  • Work with visualization data to present complex biological information in an intuitive manner.
  • Leverage expertise in metabolic diseases, wet lab science, and multidisciplinary research to extract insights from biological data.
  • Utilise next-generation sequencing (NGS) data to study molecular structures and optimise engineering approaches.
  • Collaborate with biologists, data scientists, and engineers to drive innovative research and applications.
  • Implement and optimise machine learning models for biological data interpretation.
  • Work with large-scale biological datasets, ensuring accuracy and efficiency in data processing and analysis.

Essential Qualifications & Experience:

  • PhD in Computational Biology, Bioinformatics, Data Science, or a related field.
  • Strong background in biological data analysis with hands-on experience.
  • Proficiency in machine learning (ML), Python, and related computational tools.
  • Prior experience working with bio data and understanding biological processes.
  • Familiarity with NGS technologies and sequencing data analysis (a major advantage).
  • Ability to develop robust and scalable data processing pipelines.
  • Strong problem-solving skills and the ability to work in a fast-paced environment.

Desirable Skills:

  • Experience in developing and applying protein language models.
  • Knowledge of multi-disciplinary research approaches combining computational and experimental techniques
  • Understanding of metabolic diseases and relevant biological pathways.
  • Experience with wet lab environments and translating biological findings into computational models.

The role is offering a salary of up to £75,000 per annum and comes with a wealth of benefits.

Please apply within.

Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates

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In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.