Genomics ML Research Assistant: GC Bias & Recombination in Oxford

Genomics ML Research Assistant: GC Bias & Recombination in Oxford

Oxford Full-Time 63000 - 77000 £ / year (est.) No working from home possible
Economics Network

At a Glance

  • Tasks: Develop machine-learning methods to explore gene conversion and recombination in human genetics.
  • Company: Join the prestigious Hinch Group at the University of Oxford.
  • Benefits: Gain valuable research experience and collaborate with leading experts in the field.
  • Other info: Collaborative environment with opportunities for personal and professional growth.
  • Why this job: Make a real impact in genomics while working on exciting, cutting-edge research.
  • Qualifications: Experience in machine learning and a passion for genetics is essential.

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

The Hinch Group at the Sir William Dunn School of Pathology, University of Oxford, invites applications for a Research Assistant to develop machine-learning approaches to investigate GC-biased gene conversion and meiotic recombination in human genetics.

You will analyse large-scale genomic datasets, implement computational methods, and work closely with a collaborative team to address fundamental questions in molecular evolution.

Genomics ML Research Assistant: GC Bias & Recombination in Oxford employer: Economics Network

The University of Worcester is an excellent employer, offering a supportive and collaborative work culture that values innovation in education. As a PGCE Secondary Science Lecturer, you will have the opportunity to inspire future educators while benefiting from professional development and a flexible part-time schedule at our vibrant St John’s Campus. Join us to make a meaningful impact in the field of education and enjoy a comprehensive benefits package tailored for your needs.

Economics Network

Contact Details:

Economics Network Recruitment Team

We think you need these skills to ace Genomics ML Research Assistant: GC Bias & Recombination in Oxford

Machine Learning
Genomic Data Analysis
Computational Methods
Collaboration Skills
Molecular Evolution Knowledge
Data Handling
Statistical Analysis