Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead groundbreaking analyses in genetics and collaborate with diverse teams to drive drug discovery.
- Company: Cutting-edge techbio on a mission to revolutionise health resilience.
- Benefits: Competitive salary, innovative projects, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and innovation.
- Why this job: Join a pioneering team using AI to unlock novel therapies and make a real impact.
- Qualifications: MSc or PhD in relevant fields and 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 Leeds 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 Leeds
✨Tip Number 1
Get to know the company inside out! Research their mission, values, and recent projects. This will help you tailor your conversations and show that you're genuinely interested in their work.
✨Tip Number 2
Network like a pro! Connect with current employees on LinkedIn or attend industry events. Building relationships can give you insider info and even a foot in the door for that Statistical Geneticist role.
✨Tip Number 3
Prepare for the interview by brushing up on relevant skills and methodologies. Be ready to discuss your experience with GWAS, multi-omics, and ML techniques. We want to see how you can contribute to their cutting-edge projects!
✨Tip Number 4
Don’t forget to showcase your passion for genetics and AI during the interview. Share your thoughts on the future of drug discovery and how you can help drive their mission forward. Let’s make an impact together!
We think you need these skills to ace Statistical Geneticist - ML in Leeds
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 give us some examples!
Highlight Collaborative Experience: This position requires working cross-functionally, so if you’ve collaborated with ML, biology, or engineering teams before, let us know! We love seeing how you can contribute to a team environment and drive drug discovery decisions.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
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 your first authorships and any relevant projects you've worked on. Highlight how your contributions have driven results, especially in relation to drug discovery or genetic analysis. This will demonstrate your practical experience and analytical skills.
✨Familiarise with Tools
Since the role requires proficiency in Python/PyTorch, R, and Unix/Linux, make sure you're comfortable discussing these tools. You might even want to prepare a few examples of how you've used them in your work, particularly in building scalable pipelines or working with multi-omics data.
✨Cross-Functional Collaboration
Be ready to discuss how you've worked with different teams, such as ML, biology, and engineering. Highlight any experiences where collaboration led to successful outcomes in your projects. This shows that you can thrive in a multidisciplinary environment, which is crucial for this role.