Post-Doctoral Research Associate in Cancer Genomics

The University of Manchester; Manchester; On-site; GBP 35,000 - 50,000; Full time

Benefits offered by this job

Pension scheme

29 days annual leave + bank holidays

Ride to work scheme

EV car scheme

Job summary

The University of Manchester invites applications for a post-doctoral research associate/fellow with cancer genomics experience to join the GP-TEST-Pro study. You will analyse genomic data and calculate prostate cancer polygenic risk scores within a multidisciplinary team spanning several institutions.

Responsibilities include secure data handling, genotype QC, using PLINK/PLINK2, imputation outputs and exploring additional genomic markers.

Qualifications

• PhD in a relevant field such as genetic epidemiology, statistical genetics, bioinformatics or cancer genomics.
• Hands-on analysis of genetic/genomic datasets in cancer research.
• Experience with quality control of genotype/imputed data and population structure.

Responsibilities

• Analyse genomic data and calculate polygenic risk scores for prostate cancer.
• securely store and manage data under governance requirements.
• perform QC at sample and variant levels and assess population structure.
• use PLINK/PLINK2 and imputation outputs to clean and analyse data.
• evaluate additional genomic markers or PRS methods relevant to detection.

Skills

PhD in genetics

Cancer genomics experience

Genotype QC

PRS calculation

Genetic epidemiology concepts

Education

PhD in relevant field

Tools

PLINK/PLINK2

Imputation server outputs

Job description

We are seeking a motivated and collaborative individual to join our team as a post-doctoral research associate/fellow with cancer genomics research experience. This role offers an exciting opportunity to analyse genomic data and calculate prostate cancer polygenic risk scores for the GP-TEST-Pro study. This clinical study involves a multidisciplinary team of leading academics from the University of Manchester, Queen Mary University London, University College London, and the Institute for Cancer Research and the postholder will be working within a dynamic and inclusive environment.

You will be responsible for:

• Receiving, securely storing and managing genomic data in line with University, NHS and study governance requirements.
• Performing genotype and imputed-data quality control, including sample-level and variant-level checks, ancestry and population-structure assessment, allele harmonisation and preparation of analysis-ready datasets.
• Using appropriate genetic analysis tools, such as PLINK/PLINK2 and imputation server outputs, to clean, process and analyse genomic data.
• Calculating and validating a 451-SNV prostate cancer polygenic risk score, including harmonisation of variants, application of published effect sizes and assessment of score distribution.
• Evaluating additional genomic markers or PRS approaches relevant to clinically significant prostate cancer detection.

About You

We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate the following:

Essential Criteria:

• Have, or be about to obtain, a PhD (or equivalent) in a relevant discipline, such as genetic epidemiology, statistical genetics, bioinformatics, cancer genomics, epidemiology, data science or a related quantitative discipline
• Experience in cancer genomic medicine research, including hands‑on analysis of genetic or genomic datasets
• Experience cleaning, quality‑controlling and managing genotype or imputed genomic data, including pre‑ and post‑imputation quality checks
• Experience calculating, validating or applying polygenic risk scores using genetic variant effect sizes and appropriate ancestry or population‑structure adjustment
• Understanding of key genetic epidemiology concepts, including SNVs, alleles, imputation, linkage disequilibrium, ancestry, population structure and principal components

Desirable Criteria:

• First or co‑author publications in cancer detection research
• Experience with prostate cancer genetics, cancer risk prediction, diagnostic accuracy studies, calibration/discrimination or multivariable risk modelling
• Experience integrating genomic data with clinical, epidemiological, biomarker or imaging data
• Experience of working with PPI groups and co‑investigators
• Expertise in cancer screening or early detection research

We value transferable skills and real‑world experience as much as formal qualifications.

Our benefits include:

Generous employer contribution pension
29 days annual leave plus bank holidays, along with Christmas closure
Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits . You can also find information on our Flexible and Hybrid working here .

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy .

Enquiries about the role, shortlisting and interviews

Name: Dr Samuel Merriel

Email Address: [e-mail]

General enquiries and administrative support

[e-mail]

Technical and job portal support

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

This role is not eligible for Skilled Worker visa sponsorship. Applicants must demonstrate the right to work in the UK.

Applications close at midnight on the closing date.

Further particulars (with person specification) linked below.