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- Tasks: Develop computational methods to study treatment-resistant breast cancers using genomic data.
- Company: Join the Institute of Cancer Research, a leading cancer research institute in London.
- Benefits: Enjoy a competitive salary, professional development, and access to state-of-the-art facilities.
- Why this job: Be part of groundbreaking research that impacts cancer treatment and collaborates with top scientists.
- Qualifications: PhD in a quantitative field with experience in genomic datasets and programming skills required.
- Other info: This role offers ICR Sponsorship for visa application costs for international applicants.
The predicted salary is between 33900 - 49000 £ per year.
Salary: £39,805 to £49,023 per annum inclusive, dependent on skills and experience.
Reporting to: Dr Syed Haider
Duration of Contract: Fixed Term for 3 years in the first instance
Hours per week: 35 hours (Full Time)
Location: Chelsea
Closing Date: 13 July 2025
This role is eligible for ICR Sponsorship. Support will be provided for costs associated with Visa application.
Job Details
Under the guidance of Dr Syed Haider, we are seeking a highly motivated researcher to develop computational approaches for investigating genomic and transcriptomic determinants of heterogeneity in treatment-resistant breast cancers. The successful candidate will employ computational methods to integrate bulk and single-cell genomic/transcriptomic and imaging data to identify mechanisms of treatment resistance. The project involves computational discovery, pre-clinical investigation of therapeutic targets, and translational studies in collaboration with experimental and clinical investigators at the Breast Cancer Now Research Centre, Institute of Cancer Research, London.
About you
- PhD in a quantitative field with experience in genomic/transcriptomic datasets
- Programming and scripting skills
- Relevant experience in statistics and genetics
Department/Directorate Information
The Breast Cancer Research Data Science Team is an interdisciplinary group (~12 researchers) specializing in high-throughput data analysis, machine learning, and software engineering. We focus on identifying molecular markers of breast cancer through genomic, epigenomic, and transcriptomic data from patient samples and models, interpreting these alongside clinical data. Our work involves developing bioinformatics methods to understand treatment resistance in breast cancer. The post holder will collaborate closely with Prof. Axel Behrens’ Cancer Stem Cells laboratory.
What we offer
- A dynamic and supportive research environment
- Access to state-of-the-art facilities and professional development
- Collaboration with leading researchers
- Competitive salary and pension
We encourage all applicants to access the detailed job pack attached.
About The Institute of Cancer Research
Why work for us? As a staff member, you'll enjoy a range of benefits. The ICR supports overseas applicants; further information is available. The Institute, based in London, is a leading cancer research institute with over 100 years of achievement. More about working at the ICR can be found on our website. We champion diversity and believe it fuels innovation. We welcome applicants from all backgrounds and are committed to equal opportunity employment, valuing diverse perspectives that enrich our work. If you’re passionate about this role, we want to hear from you—your unique experiences contribute to our team. We strive to create an inclusive environment where everyone’s voice is valued.
Analytical Scientist in Computational Genomics employer: The Institute Of Cancer Research
Contact Detail:
The Institute Of Cancer Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytical Scientist in Computational Genomics
✨Tip Number 1
Familiarise yourself with the latest advancements in computational genomics, particularly in relation to breast cancer research. This will not only enhance your understanding but also allow you to engage in informed discussions during interviews.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or webinars. Building connections can provide insights into the role and may even lead to referrals, increasing your chances of landing the job.
✨Tip Number 3
Prepare to discuss specific projects or experiences where you've successfully applied programming and statistical skills to genomic datasets. Highlighting these examples will demonstrate your practical expertise and problem-solving abilities.
✨Tip Number 4
Research Dr Syed Haider's work and the Breast Cancer Research Data Science Team's recent publications. Being knowledgeable about their projects will show your genuine interest in the role and help you articulate how you can contribute to their goals.
We think you need these skills to ace Analytical Scientist in Computational Genomics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD and relevant experience in genomic/transcriptomic datasets. Emphasise your programming skills and any statistical or genetics experience that aligns with the job description.
Craft a Compelling Cover Letter: Write a cover letter that specifically addresses the role of Analytical Scientist in Computational Genomics. Discuss your motivation for applying, your research interests, and how your background makes you a suitable candidate for the position.
Highlight Collaborative Experience: Since the role involves collaboration with other researchers, mention any previous teamwork or interdisciplinary projects you've been involved in. This will demonstrate your ability to work effectively within a team.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for spelling and grammatical errors, and ensure that all information is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at The Institute Of Cancer Research
✨Showcase Your Technical Skills
Make sure to highlight your programming and scripting skills during the interview. Be prepared to discuss specific projects where you've used these skills, especially in relation to genomic or transcriptomic datasets.
✨Demonstrate Your Research Experience
Discuss your PhD research and any relevant experience you have in statistics and genetics. Be ready to explain how your background aligns with the role's focus on treatment-resistant breast cancers.
✨Familiarise Yourself with the Team's Work
Research the Breast Cancer Research Data Science Team and their recent publications. Understanding their methodologies and goals will help you articulate how you can contribute to their ongoing projects.
✨Prepare Questions for Your Interviewers
Think of insightful questions to ask Dr Syed Haider and other team members. This shows your genuine interest in the role and helps you assess if the environment is a good fit for you.
