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- 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 environment with a focus on collaboration and cutting-edge technology.
- 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
- 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
- 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 Guildford 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 Guildford
✨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 lead to opportunities that aren’t even advertised yet.
✨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 gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing answers to common questions about GWAS, ML, and your experience with large datasets. The more comfortable you are, the better you'll perform.
✨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 connect directly with us.
We think you need these skills to ace Statistical Geneticist - ML in Guildford
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’s a big plus!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Highlight your key achievements and how they relate to the responsibilities of the role.
Apply Through Our Website: We encourage you to apply directly through our website. It makes the process smoother for both of us! Plus, it ensures that your application gets the attention it deserves. Don’t forget to prepare for a chat about your skills and experiences!
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 experience and analytical skills.
✨Familiarise 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 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.