Research Associate in Bioinformatics

Job reference: BMH-030198
Salary: £37,694 - £41,064 per annum, depending on relevant experience
Faculty/Organisational Unit: Biology, Medicine Health
Location: Oglesby Cancer Research Building, 555 Wilmslow Road, M20 4GJ
Employment type: Fixed Term
Division/Team: Division of Cancer Sciences
Hours Per Week: 1 FTE
Closing date (DD/MM/YYYY): 20/11/2025
Contract Duration: available from January 2026 for 4 years
School/Directorate: School of Medical Sciences

You will join the MCP group and contribute to one of our research themes, aimed at discovering how biology influences pathological response to neoadjuvant chemotherapy in advanced HGSOC. You will analyse data generated from imaging mass cytometry used on patient biopsies to answer key research questions focussed on chemotherapy response score (CRS). You will develop an AI/machine learning model using spatial proteomics that can accurately differentiate CRS phenotypes. You will have an opportunity to apply the AI/machine learning algorithm to tissue microarrays built from patients recruited to the phase 3 trial, ICON8b. Thus, you will have a unique opportunity to use a cutting-edge technology to perform deep phenotyping of a clinically-validated treatment response biomarker for HGSOC, resolving the tumour microenvironment of CRS at the single-cell level and helping to develop a new molecular test to stratify first-line therapy.

The project aligns with our core research programmes. Indeed, the MCP group have built the largest national biobank of primary cell cultures, donated by 150 patients treated for ovarian cancer at The Christie hospital. This Living Biobank is clinically annotated, and all chemotherapy naïve samples have undergone whole genome sequencing (WGS), single-cell WGS, RNA-seq and bulk proteomics. The Living Biobank provides a unique resource that underpins our research strategy: to identify cell cycle vulnerabilities in HGSOC that can be exploited using targeted therapies and develop new biomarkers that can personalize cancer care. You will have access to multiomic data generated from the Living Biobank, if required.

We welcome applications from candidates with or without prior experience in ovarian cancer research. You will have bioinformatic expertise, including experience using R and/or Python. High attention to detail is essential, as well as an ambition to produce high-quality research, including presentations at international and national conferences, and manuscripts for peer-reviewed publications. Importantly, the successful applicant will be a good team player.

What will you 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

As an equal opportunity employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.

Please be aware that due to the number of applications we are unfortunately not able to provide individual feedback on your application.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr Robert Morgan

Email: robert.morgan7@nhs.net

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

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