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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 work environment, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a collaborative setting.
- Why this job: Join a pioneering team using AI and genetics to make a real impact in healthcare.
- 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 Maidstone 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 Maidstone
✨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 that 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. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 4
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 connect directly with us. Don’t forget to tailor your CV to highlight your relevant experience!
We think you need these skills to ace Statistical Geneticist - ML in Maidstone
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: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
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. This will demonstrate your practical skills and analytical background.
✨Familiarise with the Tech Stack
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 past projects, particularly in relation to deep learning or cloud computing.
✨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.