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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 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 Telford 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 Telford
✨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 and ML 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. Bring along examples of your work with large-scale genetic datasets or any pipelines you've built – it’ll show you mean business!
✨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. Let’s get you that Statistical Geneticist role!
We think you need these skills to ace Statistical Geneticist - ML in Telford
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 include specific examples where possible.
Highlight Collaborative Experience: This position requires working cross-functionally, so if you’ve collaborated with ML, biology, or engineering teams before, make it known! We love seeing candidates who can work well with others to drive drug discovery decisions.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our mission to unlock novel therapies.
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 QTL data types. Be ready to discuss how you've applied these methodologies in your previous work, as well as any hands-on experience with large-scale genetic datasets.
✨Showcase Your Technical Skills
Since the role requires proficiency in Python/PyTorch, R, and Unix/Linux, be prepared to demonstrate your coding skills. You might even want to bring along a portfolio or examples of your work that highlight your experience with these tools.
✨Collaborative Spirit
This position involves working cross-functionally with ML, biology, and engineering teams. Think of examples from your past where you successfully collaborated with different departments, and be ready to share how you can contribute to a team environment.
✨Prepare for Deep Learning Discussions
Given the emphasis on deep learning and ML, make sure you can discuss relevant projects or research you've been involved in. Highlight any experience with HPC or cloud computing, as this will show you're well-versed in the technical aspects of the role.