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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 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:
- 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 Lincoln 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 Lincoln
✨Tip Number 1
Get your networking game on! Reach out to professionals in the field of statistical genetics and AI. Use platforms like LinkedIn to connect with people at Wenham Carter or similar companies. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Prepare for those interviews! Brush up on your knowledge of GWAS, PheWAS, and multi-omics data integration. Be ready to discuss how your experience with Python, R, and machine learning can contribute to their mission of driving drug discovery.
✨Tip Number 3
Showcase your projects! If you've worked on relevant research or have hands-on experience with large-scale genetic datasets, make sure to highlight these during your conversations. Bring along examples that demonstrate your skills in building scalable pipelines.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in the role and the company. Let’s get you that job!
We think you need these skills to ace Statistical Geneticist - ML in Lincoln
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Statistical Geneticist role. Highlight your experience with GWAS, multi-omics, and any relevant projects that showcase your analytical skills. We want to see how your background aligns with our mission!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of your work with Python, R, or any ML techniques you've used. This helps us understand how you can contribute to our cutting-edge techbio environment.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's necessary. We appreciate straightforward communication that gets to the heart of your experience.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
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, like Python, PyTorch, R, and Unix/Linux. Be prepared to answer technical questions or even solve problems on the spot to showcase your proficiency and problem-solving skills.