Research Associate in Breast Cancer Prevention
Publicerad 2025-03-08
Job Title: Research Associate in Breast Cancer Prevention
Job Location: Manchester, UK
Job Location Type: Hybrid
Job Contract Type: Full-time
Job Seniority Level: Entry level
The post is funded through a Cancer Research UK Biology to Prevention project grant. The key questions we aim to answer are:
What structural features define high-risk breast tissue, and can these be identified by mammography?
Can we predict responders and non-responders prior to prevention treatment?
Can an understanding of the biology of risk identify novel prevention targets?
The project will employ two parallel strategies. One will be to undertake high resolution analysis of breast tissue composition and its response to tamoxifen. The second will be to use machine learning analysis of serial mammograms collected in large screening programs. This specific post will be focussed on the first approach.
The purpose of this role will be:
What you will get in return:
Our University is positive about flexible working – you can find out more here
Hybrid working arrangements may be considered.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Any CV’s submitted by a recruitment agency will be considered a gift.
Enquiries about the vacancy, shortlisting and interviews:
Email: or
General enquiries:
Email:
Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
What structural features define high-risk breast tissue, and can these be identified by mammography?
Can we predict responders and non-responders prior to prevention treatment?
Can an understanding of the biology of risk identify novel prevention targets?
The project will employ two parallel strategies. One will be to undertake high resolution analysis of breast tissue composition and its response to tamoxifen. The second will be to use machine learning analysis of serial mammograms collected in large screening programs. This specific post will be focussed on the first approach.
The purpose of this role will be:
- Identify the biological features of resistance to preventive tamoxifen in breast tissue biopsies.
- Define the mechanistic effect of tamoxifen to identify novel prevention targets using ex vivo explant cultures.
What you will get in return:
- Fantastic market leading Pension scheme
- Excellent employee health and wellbeing services including an Employee Assistance Programme
- Exceptional starting annual leave entitlement, plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at a range of major retailers
Our University is positive about flexible working – you can find out more here
Hybrid working arrangements may be considered.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Any CV’s submitted by a recruitment agency will be considered a gift.
Enquiries about the vacancy, shortlisting and interviews:
Email: or
General enquiries:
Email:
Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
Lifelancer ( https://lifelancer.com ) is a talent-hiring platform in Life Sciences, Pharma and IT. The platform connects talent with opportunities in pharma, biotech, health sciences, healthtech and IT domains.
For more details and to find similar roles, please check out the below Lifelancer link.
https://lifelancer.com/jobs/view/760d8a2b6a52d642344dc518f15cca40