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For Companies At a Glance
- Tasks: Lead groundbreaking analyses in genetics and collaborate with diverse teams to drive drug discovery.
- Company: Join a cutting-edge techbio on a mission to revolutionise health resilience.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and innovation.
- Why this job: Make a real impact in healthcare by unlocking novel therapies through innovative research.
- 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.
Locations
Statistical Geneticist - ML in Cheshire, Warrington 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 Cheshire, Warrington
✨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 open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects in Python, R, or any relevant tools. This is your chance to demonstrate your hands-on experience with large-scale datasets and ML techniques.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on GWAS methodologies and multi-omics data integration. Mock interviews with friends or mentors can help you articulate your experience confidently.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Statistical Geneticist - ML in Cheshire, Warrington
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 love seeing candidates who can demonstrate their ability to work with ML and deep learning tools, so include specific examples where you’ve applied these skills.
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 appreciate candidates who can communicate their teamwork experiences and how they contributed to successful projects.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy – just upload your CV and let us know why you’re a great fit!
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 through how you would approach specific problems related to genetic analysis.
✨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 a techbio or research setting. Emphasise your ability to communicate complex ideas clearly to non-experts.