Job Summary Table of Postdoctoral Research Associate in Statistical Genomics

Job Description Summary

The University of Oxford is seeking a talented Postdoctoral Research Associate to join the Germline Genomics laboratory at the Sir William Dunn School of Pathology. This role offers an exciting opportunity to contribute to cutting-edge research in statistical genomics, focusing on understanding DNA changes in human cells and their impacts on health and evolution.

Responsibilities

• Develop statistical models and machine learning algorithms for analyzing large-scale genomic datasets
• Apply these models to human genetic variation data, chromatin and epigenetic maps, protein binding data, and disease traits
• Lead independent research projects within the scope of the laboratory’s focus
• Collaborate with international partners and present findings at conferences and workshops
• Contribute to the publication of research results in high-impact scientific journals
• Assist in mentoring junior researchers and students in the laboratory

Benefits and Perks

• Competitive salary range of £36,024 – £44,263 per annum
• Access to world-class research facilities and resources at the University of Oxford
• Opportunities for professional development and networking with leading scientists in the field
• Potential for international travel to attend conferences and collaborate with partners
• Supportive and stimulating research environment in a prestigious institution

Company Overview

The University of Oxford is a world-renowned center for education and research, consistently ranking among the top universities globally. With a rich history dating back to the 11th century, Oxford continues to be at the forefront of scientific discovery and innovation.

Company Culture

At the Sir William Dunn School of Pathology, we foster a collaborative and intellectually stimulating environment. Our researchers are encouraged to think creatively, push boundaries, and contribute to groundbreaking discoveries in the field of genomics and pathology.

Career Growth Opportunities

This position offers excellent prospects for career advancement in the field of statistical genomics and computational biology. You will have the chance to:

• Develop expertise in cutting-edge genomic analysis techniques
• Build a strong publication record in high-impact journals
• Establish valuable connections within the international scientific community
• Gain experience in project leadership and mentoring
• Potentially transition to independent research positions or roles in biotechnology and pharmaceutical industries

Diversity, Equity, Inclusion, and Belonging

The University of Oxford is committed to fostering an inclusive culture that promotes equality, values diversity, and maintains a working, learning, and social environment in which the rights and dignity of all its staff and students are respected.

Equal Opportunity Statement

The University of Oxford is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status.

Remote Work Policy

This position requires on-site presence at the Sir William Dunn School of Pathology in Oxford. However, the university supports flexible working arrangements where possible, subject to the needs of the role and agreement with the supervisor.

Application Process

1. Review the job description and ensure you meet the essential criteria
2. Prepare your CV and a supporting statement
3. Apply online through the University of Oxford’s recruitment portal
4. If shortlisted, participate in an interview process

Application Deadline

The closing date for applications is midday on 31 July 2024. We encourage early applications as interviews may be conducted on a rolling basis.

How to Apply

To apply for this position, please visit the University of Oxford’s job portal and follow the application instructions. You will need to upload your CV and a supporting statement as part of your online application.

Social Media Links

• University of Oxford LinkedIn
• University of Oxford Twitter
• University of Oxford Facebook

FAQs or Additional Information

Q: What qualifications are required for this position?

A: Candidates should hold, or be close to completing, a PhD/DPhil in a quantitative discipline such as statistics, applied mathematics, physics, or computer science.

Q: Is experience in genetics or genomics necessary?

A: While a strong interest in biological problems, genetics, and/or genomics is essential, previous experience in these fields is not required. The ideal candidate will have a strong background in statistical methods and programming.

Q: What is the duration of the contract?

A: The post is initially available as a fixed-term contract for 2 years, with the possibility of extension.

Q: Can I contact someone for more information about the position?

A: Yes, for informal inquiries about the position or the project, you can contact Dr. Anjali Hinch at anjali.hinch@path.ox.ac.uk.

Q: Where can I find more information about the research group?

A: You can visit the Germline Genomics laboratory website at for more information about ongoing research and publications.

Join us at the University of Oxford and be part of groundbreaking research that is shaping our understanding of genomics and its impact on human health. This postdoctoral position offers a unique opportunity to work with world-class scientists, access cutting-edge resources, and contribute to discoveries that could revolutionize our approach to genetic diseases and cancer treatment.

As a Postdoctoral Research Associate in Statistical Genomics, you’ll be at the forefront of unraveling the mysteries of DNA changes in human cells. Your work will have far-reaching implications, from understanding inherited diseases to shedding light on the evolutionary processes that have shaped our species.

Don’t miss this chance to advance your career in one of the world’s most prestigious academic institutions. Apply now and take the next step towards becoming a leader in the field of statistical genomics!

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