At a Glance
- Tasks: Revolutionise drug discovery by developing tools and workflows that analyse complex biological data.
- Company: Join Recursion, a pioneering company transforming healthcare through innovative technology.
- Benefits: Competitive salary, annual bonus, equity compensation, and comprehensive benefits package.
- Other info: Hybrid role based in London with excellent career growth opportunities.
- Why this job: Make a real impact on patients' lives while working with cutting-edge data and technology.
- Qualifications: PhD in relevant field or equivalent experience; strong skills in computational biology and data analysis.
The predicted salary is between 86300 - 115500 ÂŁ per year.
Your work will change lives. Including your own.
The Team You’ll Join
As part of Recursion's Value Tech Tooling Team, you will be at the forefront of reimagining drug discovery from first principles using our massive data capabilities. You'll work in a cross-functional team of world‑class computational biologists and engineers who turn complex analyses and data workflows into stable tools and pipelines that multiply their impact and industrialise the discovery process across a wide array of therapeutic areas. You'll partner with biologists, medicinal chemists, engineers, data scientists, ML scientists, and analyse experiments, develop new methods, build scalable data workflows, analyse results, and identify common themes across programs. As our toolbox grows and evolves it will contribute to a revolution in drug discovery to bring life‑changing therapeutics to patients at greater speed and with higher quality, safety and efficacy than ever before.
In this role, you will:
- Synthesize, integrate, and analyse diverse internal and external datasets from computational biology, target discovery, functional genomics, biomarker discovery, and real‑world and clinically derived data sources, and identify commonalities to turn into reusable tools and pipelines.
- Build, maintain, and improve robust data pipelines and analytical workflows for complex biological datasets, including omics data, internally generated biological assay data, and external data sources such as Tempus and other real‑world datasets.
- Develop and apply agentic workflows to integrate and orchestrate analyses across multiple internal and external data sources, accelerating insight generation and supporting scalable decision‑making across drug discovery programs.
- Partner with engineers to mature pilot tooling and workflows into stable products and infrastructure that multiply the effectiveness of scientific collaborators pursuing drug programs.
- Present and discuss data, pipelines, and tools with decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients.
- Collaborate cross‑functionally with Recursion’s platform data science, data engineering, and ML teams to further advance Recursion’s ability to interpret and translate large‑scale phenomics and multimodal data into therapeutic programs.
The Experience You’ll Need
- PhD in a relevant field (e.g., computational biology, bioinformatics, statistics, quantitative pharmacology, cancer/cell biology, computer science, or a related discipline), or equivalent experience, with a track record of applying these skills to fundamental problems in drug discovery.
- Experience applying computational methods (including statistical, probabilistic, and/or machine learning techniques) to analyse complex biological and/or human clinical data.
- Experience building, maintaining, and improving reproducible data pipelines and analytical workflows for large, heterogeneous biological datasets (Python strongly preferred).
- Experience working with high‑dimensional biological datasets, including omics data (e.g., single‑cell and other genomics‑based modalities) and/or other complex assay modalities.
- Experience turning exploratory analyses into reusable tools, workflows, and documentation that can be adopted by other scientists/teams.
- General understanding of drug discovery and translational biology.
Nice To Have
- Experience working on highly collaborative cross‑functional teams; ability to clearly explain computational analyses, data workflows, and methodologies to cross‑functional and non‑technical teams.
- Hands‑on experience working with real‑world clinical datasets (EHR/claims/registries) and/or generating real‑world evidence (cohorting, endpoint definition, observational study considerations).
- Experience with real‑world clinical datasets (e.g., EHR‑derived oncology datasets) or demonstrated ability to rapidly learn new healthcare data modalities; experience with Tempus or similar datasets is a plus.
- Experience integrating multimodal datasets (e.g., genomics + phenomics, genomics + imaging) in service of translational decisions.
- Experience developing or applying agentic workflows to orchestrate analyses across multiple internal and external data sources, accelerating insight generation and decision‑making.
Location and Compensation
This is an office‑based, hybrid position at our office located in London, England. Employees are expected to work in the office at least 50% of the time. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is £86,300 - £115,500. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package.
Recursion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation. Accommodations are available on request for candidates taking part in all aspects of the selection process.
Senior Computational Biologist, Tooling in London employer: Menlo Ventures
Contact Detail:
Menlo Ventures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computational Biologist, Tooling in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend relevant meetups, and engage with professionals on platforms like 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 related to computational biology and data workflows. This will give potential employers a tangible sense of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with cross-functional teams. Mock interviews can be a game changer!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Recursion.
We think you need these skills to ace Senior Computational Biologist, Tooling in London
Some tips for your application 🫡
Show Your Passion: Let us see your enthusiasm for computational biology and drug discovery! Share specific examples of how your work has made an impact in the field, and why you're excited about the opportunity to join our team.
Tailor Your Application: Make sure to customise your CV and cover letter to highlight the skills and experiences that align with the job description. We want to see how your background fits into our mission of revolutionising drug discovery!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to describe your experiences and achievements, so we can easily understand your qualifications and how you can contribute to our team.
Apply Through Our Website: We encourage you to submit your application directly through our website. This way, you’ll ensure that your application reaches us promptly and is considered for the role you’re interested in!
How to prepare for a job interview at Menlo Ventures
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of datasets mentioned in the job description, especially omics and clinical data. Be prepared to discuss your experience with these datasets and how you've used them in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, think of examples where you've successfully collaborated with biologists, engineers, or data scientists. Highlight how you communicated complex analyses to non-technical team members.
✨Prepare for Technical Questions
Brush up on your computational methods, especially statistical and machine learning techniques. Be ready to explain how you've applied these methods to solve real-world problems in drug discovery.
✨Present Your Work Clearly
Practice explaining your previous projects and tools in a clear and compelling way. You might be asked to present your findings, so focus on how you can drive insights that lead to actionable decisions in drug discovery.