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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 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
- 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 Preston 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 Preston
✨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 chat can sometimes lead to opportunities that aren’t even advertised!
✨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 any relevant research or personal projects, make sure to highlight them. Having a portfolio or GitHub repository can really set you apart and demonstrate your hands-on experience with large-scale datasets.
✨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 take the initiative to engage directly with us. Good luck!
We think you need these skills to ace Statistical Geneticist - ML in Preston
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 methodologies. If you've worked with cloud computing or HPC, let us know – it could really set you apart!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see how your experience fits the role without wading through unnecessary details.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our mission to drive drug discovery with cutting-edge tech!
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. Real examples will make you stand out!
✨Get Technical
Since the role requires skills in Python/PyTorch, R, and Unix/Linux, be prepared for technical questions or even a coding challenge. Brush up on your coding skills and think of ways to demonstrate your proficiency during the interview.
✨Collaborative Mindset
This position involves working cross-functionally with various teams. Be ready to discuss how you've successfully collaborated with others in the past, particularly in driving drug discovery decisions. Show that you're a team player who can communicate effectively across disciplines.