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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 and therapies.
- 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:
- 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 in Bournemouth 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 Bournemouth
✨Tip Number 1
Get your networking game on! Connect with professionals in the field of statistical genetics and AI. Attend relevant meetups or webinars, and don’t be shy to reach out on LinkedIn. You never know who might have a lead on that perfect job!
✨Tip Number 2
Prepare for those interviews like a pro! Brush up on your knowledge of GWAS, PheWAS, and multi-omics. Be ready to discuss your hands-on experience with large-scale datasets and how you’ve applied ML techniques in your past work. Confidence is key!
✨Tip Number 3
Showcase your projects! If you’ve built any pipelines or worked on genetic analyses, make sure to highlight these in conversations. Having tangible examples of your work can really set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you. Make sure your CV is updated and tailored to the role, and let’s get you one step closer to landing that dream job!
We think you need these skills to ace Statistical Geneticist - ML in Bournemouth
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 ML or deep learning. We’re looking for candidates who can hit the ground running, so let us know what tools you’re comfortable with!
Highlight Collaborative Experience: This position requires working cross-functionally, so if you’ve collaborated with teams in biology, engineering, or ML, make it known! We love seeing how you’ve contributed to team efforts in past roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore 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 your first authorships and any relevant projects you've worked on. Highlight how your contributions have driven results, especially in relation to drug discovery or genetic analysis. This will demonstrate your practical experience and analytical skills.
✨Familiarise Yourself with Tools
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 your work, particularly in building scalable pipelines for population-scale datasets.
✨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.