At a Glance
- Tasks: Revolutionise drug discovery by developing tools and workflows for complex biological data.
- Company: Join Recursion, a leader in innovative drug discovery technology.
- Benefits: Competitive salary, annual bonus, equity compensation, and comprehensive benefits package.
- Other info: Hybrid role in London with excellent career growth opportunities.
- Why this job: Make a real impact on patients' lives through cutting-edge research and collaboration.
- Qualifications: PhD or equivalent experience in computational biology or related fields.
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 employer: Menlo Ventures
Contact Detail:
Menlo Ventures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computational Biologist, Tooling
✨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 practising common questions and scenarios specific to drug discovery and computational biology. Think about how you can articulate your experience with data pipelines and cross-functional collaboration clearly.
✨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
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for computational biology and drug discovery shine through. We want to see how your experiences and interests align with our mission to change lives!
Tailor Your CV: Make sure your CV highlights relevant experience that matches the job description. We love seeing how you've applied your skills in real-world scenarios, especially in building data pipelines or working with complex datasets.
Be Clear and Concise: In your written application, clarity is key! Use straightforward language to explain your past projects and achievements. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity on our team.
How to prepare for a job interview at Menlo Ventures
✨Know Your Data
Make sure you’re well-versed in the types of datasets mentioned in the job description, like omics data and real-world clinical datasets. Brush up on your experience with Python for building data pipelines, as this will likely come up during technical discussions.
✨Showcase Collaboration Skills
Since this role involves working with cross-functional teams, be prepared to discuss your past experiences collaborating with biologists, engineers, and data scientists. Highlight specific projects where you successfully communicated complex analyses to non-technical team members.
✨Prepare for Technical Questions
Expect questions about computational methods and statistical techniques you've applied in previous roles. Be ready to explain how you’ve turned exploratory analyses into reusable tools and workflows, as this is a key part of the job.
✨Communicate Clearly
Practice presenting your past work in a clear and compelling way. You might need to explain your data workflows and methodologies to decision-makers, so focus on making your explanations straightforward and engaging.