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- 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 work environment, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a collaborative setting.
- 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:
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 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
✨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 ML work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by brushing up on your knowledge of GWAS, PheWAS, and other relevant methodologies. Being able to discuss these confidently will set you apart.
✨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
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 we're looking for someone with a strong analytical background, be sure to mention your proficiency in Python, R, and any experience with ML or deep learning. We love seeing candidates who can demonstrate their technical prowess, especially in relation to GWAS methodologies.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and how they fit the role. Avoid jargon unless it's relevant to the position!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the position. Plus, it gives you a chance to check out more about our mission and values.
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 used Python, R, or any relevant tools. Highlight your 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, think of examples where you've successfully collaborated with teams from different backgrounds, like biology or engineering. This will show that you're a team player and can drive drug discovery decisions effectively.
✨Ask Smart Questions
Prepare insightful questions about the company's mission and their approach to integrating multi-omics data. This not only shows your interest but also helps you gauge if the company aligns with your career goals.