At a Glance
- Tasks: Lead groundbreaking analyses in genetics and collaborate with diverse teams to drive drug discovery.
- Company: Cutting-edge techbio focused on health resilience and innovative therapies.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and innovation.
- Why this job: Join a mission-driven 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
- 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 Oxford employer: Searches @ Wenham Carter
Wenham Carter offers an exceptional work environment for a Statistical Geneticist, where innovation meets collaboration in the vibrant techbio sector. Employees benefit from a culture that prioritises professional growth, with opportunities to engage in groundbreaking research and development alongside leading pharma partners. Located in a dynamic area, the company fosters a supportive atmosphere that encourages creativity and the pursuit of novel therapies, making it an ideal place for those seeking meaningful and impactful careers.
StudySmarter Expert Advice🤫
We think this is how you could land Statistical Geneticist - ML in Oxford
✨Tip Number 1
Network like a pro! Reach out to folks 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 brushing up on your knowledge of GWAS, PheWAS, and ML techniques. Being able to discuss these topics confidently will set you apart from the crowd.
✨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 are proactive about their job search.
We think you need these skills to ace Statistical Geneticist - ML in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in statistical genetics and any hands-on work with large-scale datasets. We want to see how your skills align with the role, so don’t be shy about showcasing your first authorships and technical proficiencies!
Showcase Your Analytical Skills:In your application, emphasise your analytical background and any specific projects where you've led GWAS or integrated multi-omics data. We’re looking for candidates who can demonstrate their ability to drive genetic discovery through solid examples.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and experiences without wading through unnecessary fluff.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the position. Plus, it shows you’re keen on 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 methodologies 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.
✨Collaborative Spirit
Since the role involves working cross-functionally, think of examples where you've successfully collaborated with teams from different backgrounds, like biology or engineering. Share how you communicated complex ideas effectively and contributed to drug discovery decisions.
✨Technical Proficiency
Be ready to discuss your proficiency in Python, R, and any experience with cloud computing or HPC. You might be asked to solve a problem on the spot, so practice coding challenges related to statistical genetics and machine learning to showcase your skills.
