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 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:
- Lead GWAS, PheWAS, PRS, rare variant and post‑GWAS analyses
- Integrate multi‑omics QTL data (eQTL, pQTL, mQTL) for gene prioritisation and causal inference
- Working with and 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 Glasgow 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 Glasgow
✨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 might even lead to a referral.
✨Tip Number 3
Prepare for the interview by practising common questions related to statistical genetics and machine learning. We recommend using the STAR method to structure your answers and highlight your relevant experience.
✨Tip Number 4
Don’t forget to follow up after your interview! A quick thank-you email can leave a lasting impression and keep you top of mind as they make their decision.
We think you need these skills to ace Statistical Geneticist - ML in Glasgow
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 love seeing candidates who can demonstrate their ability to work with ML and deep learning tools, so include specific examples where you’ve applied these skills.
Highlight Collaborative Experience: This position requires working cross-functionally with various teams, so it’s important to highlight any collaborative projects you've been part of. Share examples of how you’ve worked with biology or engineering teams to drive results, as we value teamwork at StudySmarter!
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 submit – 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 your first authorships and any relevant projects you've worked on. Highlight how your contributions have driven results, especially in integrating multi-omics data or building scalable pipelines. This will demonstrate your practical skills and analytical background.
✨Familiarise with the Tech Stack
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 past projects, particularly in relation to deep learning or cloud computing.
✨Collaborative Mindset
This position involves working cross-functionally with various teams. Be prepared to share examples of how you've successfully collaborated with others, whether in ML, biology, or engineering. Emphasising your teamwork skills will show that you're a great fit for their culture.