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- Tasks: Lead groundbreaking analyses in genetics and collaborate with diverse teams to drive drug discovery.
- Company: Join a cutting-edge techbio on a mission to revolutionise health resilience.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and innovation.
- Why this job: Make a real impact in healthcare by unlocking novel therapies through innovative research.
- Qualifications: MSc or PhD in relevant fields and hands-on experience with large-scale genetic datasets.
The predicted salary is between 60000 - 80000 £ per year.
Wenham Carter are partnered with a cutting-edge techbio, on a mission to model health resilience, unlocking novel therapies. Combining large-scale human genetics, multi‑omics, and AI, they are driving target discovery and accelerating drug development in partnership with leading pharma companies. They are hiring a Statistical Geneticist with a strong analytical background to a key role in their genetics‑driven causal AI platform:
- Responsibilities
- Lead GWAS, PheWAS, PRS, rare variant and post‑GWAS analyses
- Integrate multi‑omics QTL data (eQTL, pQTL, mQTL) for gene prioritisation and causal inference
- Apply ML‑derived and continuous phenotypes to enhance genetic discovery
- Build scalable, reproducible pipelines for population-scale datasets
- Work cross‑functionally with ML, biology, and engineering teams to drive drug discovery decisions
- What we’re looking for
- MSc or PhD in Statistical Genetics, Bioinformatics, Biostatistics, or similar. First authorships on published papers particularly interesting
- Hands-on experience with large-scale genetic datasets
- Demonstrated skills & experience in Python/PyTorch, R, Unix/Linux, and GWAS methodologies
- Experience with HPC or cloud computing
- Experience in deep learning or ML.
Please apply with an updated CV to be considered for the position. Be prepared to talk through your skills and experience which aligns with the position.
Statistical Geneticist - ML in Doncaster employer: Searches @ Wenham Carter
Contact Detail:
Searches @ Wenham Carter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Statistical Geneticist - ML in Doncaster
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in techbio or genetics. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects in Python, R, or any relevant tools. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing answers to common questions about GWAS, ML applications, and your experience with large datasets. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Statistical Geneticist - ML in Doncaster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in statistical genetics and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your first authorships and hands-on experience with large-scale datasets!
Showcase Your Technical Skills: Since this role involves a lot of technical work, be sure to mention your proficiency in Python, R, and any experience with GWAS methodologies. We’re keen to see how you’ve applied these skills in real-world scenarios, so include specific examples where possible.
Highlight Collaborative Experience: This position requires working cross-functionally, so if you’ve collaborated with ML, biology, or engineering teams before, let us know! Share examples of how you’ve contributed to team projects and driven decisions in drug discovery.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. Make sure to double-check your application for any typos or errors before hitting send – we want to see your best work right from the start!
How to prepare for a job interview at Searches @ Wenham Carter
✨Know Your Stuff
Make sure you brush up on your knowledge of GWAS, PheWAS, and the various analyses mentioned in the job description. Be ready to discuss your hands-on experience with large-scale genetic datasets and how you've applied ML techniques in your previous work.
✨Showcase Your Projects
Prepare to talk about specific projects where you've led analyses or built pipelines for population-scale datasets. Highlight any first authorships on published papers, as this will demonstrate your expertise and commitment to the field.
✨Collaborative Spirit
Since the role involves working cross-functionally with ML, biology, and engineering teams, be ready to share examples of how you've successfully collaborated with others. Discuss how you communicate complex ideas to non-experts and how you integrate feedback into your work.
✨Technical Proficiency
Familiarise yourself with the tools and languages mentioned in the job description, like Python, PyTorch, R, and Unix/Linux. Be prepared to answer technical questions or even solve problems on the spot to showcase your proficiency.