At a Glance
- Tasks: Drive transformative insights into drug discovery using multi-omics data and advanced computational methods.
- Company: Join Relation, a pioneering TechBio company redefining medicine through technology.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with diverse teams and excellent career advancement opportunities.
- Why this job: Make a real impact on patient lives by solving complex biological problems.
- Qualifications: PhD in a quantitative field and experience with high-dimensional biological data.
The predicted salary is between 50000 - 70000 £ per year.
ABOUT RELATION
Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact.
We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.
THE OPPORTUNITY
This is a unique opportunity for a data scientist to work on multi-omics data to drive transformative insights into drug discovery. As a member of the Cross Indication team, you will contribute to identifying and validating drug targets through advanced data analysis and innovative computational approaches. The Cross Indication team collaborates across both Relations internal and partnership programmes, applying state-of-the-art computational methods to integrate diverse datasets. By combining biological insights with advanced data analytics, the team drives target discovery and validation initiative.
DAY TO DAY, YOU WILL
- Develop and implement robust computational workflows for the integration and analysis of multi-omics datasets, including single-cell and/or spatial modalities.
- Design and apply statistical and computational models for analysing transcriptomics and related omics data.
- Use biological insight and data intuition to design meaningful, challenging evaluation tasks for ML models.
- Collaborate closely with ML researchers to inform and iterate on model architectures and assumptions.
- Partner with experimental scientists to help formulate, test, and validate computational hypotheses.
- Communicate findings clearly through internal presentations and contribute to scientific publications.
PROFESSIONALLY, YOU WILL HAVE
- A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative discipline.
- Strong experience analysing high-dimensional biological data, including transcriptomics and other omics datasets.
- Proficiency in Python, with experience working in high-performance or cloud computing environments.
Bonus experience
- Experience with single-cell and/or spatial omics data, including patient-derived datasets.
- Familiarity with machine-learning approaches applied to biological data.
- A solid grounding in statistical modelling, algorithm development, or data integration methods.
- Experience working effectively within highly interdisciplinary teams spanning biology, ML, and software engineering.
PERSONALLY, YOU
- Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
- Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
- Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
- Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
- Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.
WORKING STYLE & CULTURE AT RELATION
At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting.
Data Scientist – Single Cell & Spatial (12-month FTC) in London employer: Relation
Relation is an exceptional employer, offering a unique opportunity to work at the forefront of drug discovery in a dynamic and inclusive environment. With state-of-the-art labs in the heart of London, employees benefit from a collaborative culture that fosters interdisciplinary teamwork and innovation, alongside ample opportunities for professional growth and development. By joining Relation, you will not only contribute to groundbreaking research but also be part of a mission-driven team dedicated to making a meaningful impact on patient lives.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist – Single Cell & Spatial (12-month FTC) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving multi-omics data or machine learning. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with interdisciplinary teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at Relation and contributing to groundbreaking drug discovery.
We think you need these skills to ace Data Scientist – Single Cell & Spatial (12-month FTC) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with multi-omics data and any relevant projects that showcase your skills in Python and statistical modelling. We want to see how your background aligns with our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about drug discovery and how your expertise can contribute to our team. Be sure to mention any interdisciplinary collaborations you've been part of, as we value teamwork.
Showcase Your Problem-Solving Skills:In your application, include examples of complex problems you've solved using data analysis. We love seeing how you approach challenges, especially in a matrixed environment like ours. It’s all about demonstrating your analytical mindset!
Apply Through Our Website:We encourage you to apply directly through our website. This ensures your application gets to the right people quickly. Plus, it shows us you're serious about joining our innovative team at Relation!
How to prepare for a job interview at Relation
✨Know Your Data Inside Out
Make sure you’re well-versed in the multi-omics data you'll be working with. Brush up on your knowledge of transcriptomics and spatial omics, and be ready to discuss how you've applied statistical models in past projects. This will show that you can hit the ground running!
✨Showcase Your Collaboration Skills
Since this role involves working closely with interdisciplinary teams, prepare examples of how you've successfully collaborated with others in the past. Highlight any experiences where you partnered with ML researchers or experimental scientists to solve complex problems.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Be ready to explain your experience with Python and any high-performance computing environments. Practise articulating your thought process when designing computational workflows or evaluating ML models.
✨Communicate Clearly and Confidently
Effective communication is key in this role. Prepare to present your findings clearly, as if you were addressing a mixed audience of scientists and engineers. Practise summarising complex data insights in a straightforward manner to demonstrate your ability to convey important information.