At a Glance
- 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.
- 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 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.
Statistical Geneticist - ML in Slough employer: Searches @ Wenham Carter
Wenham Carter is an exceptional employer, offering a dynamic work environment at the forefront of health resilience and drug development. With a strong emphasis on collaboration across multi-disciplinary teams, employees benefit from continuous learning opportunities and the chance to contribute to groundbreaking research that has a real-world impact. Located in a vibrant tech hub, the company fosters a culture of innovation and inclusivity, making it an ideal place for passionate individuals looking to advance their careers in statistical genetics and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Statistical Geneticist - ML in Slough
✨Tip Number 1
Get to know the company inside out! Research their mission, values, and recent projects. This will help you tailor your conversations and show that you're genuinely interested in their work.
✨Tip Number 2
Network like a pro! Connect with current employees on LinkedIn or attend industry events. Building relationships can give you insider info and even a foot in the door for that Statistical Geneticist role.
✨Tip Number 3
Prepare for those interviews by practising common questions related to statistical genetics and machine learning. We recommend having examples ready that showcase your experience with GWAS and multi-omics data.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team and contributing to their mission.
We think you need these skills to ace Statistical Geneticist - ML in Slough
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 specific projects where you've led analyses or built pipelines for population-scale datasets. Highlight any first authorships on published papers, as this will demonstrate your expertise and commitment to the field.
✨Collaborative Spirit
Since the role involves working cross-functionally with ML, biology, and engineering teams, be ready to share examples of how you've successfully collaborated with diverse teams in the past. This will show that you're a team player who can drive drug discovery decisions effectively.
✨Technical Proficiency
Familiarise yourself with the tools and languages mentioned, like Python, PyTorch, R, and Unix/Linux. Be prepared to discuss your experience with HPC or cloud computing, and if possible, bring examples of how you've used these technologies in your work.
