Statistical Geneticist - ML in Shrewsbury

Statistical Geneticist - ML in Shrewsbury

Shrewsbury Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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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 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 Shrewsbury 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.
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Contact Detail:

Searches @ Wenham Carter Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Statistical Geneticist - ML in Shrewsbury

✨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

Prepare for the interview by brushing up on your technical skills. Be ready to discuss your experience with GWAS, multi-omics, and ML techniques. We want to see how you can apply your knowledge to real-world problems!

✨Tip Number 3

Showcase your projects! If you've worked on relevant research or have hands-on experience with large-scale datasets, make sure to highlight these during your discussions. It’s all about demonstrating your impact.

✨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 Shrewsbury

Statistical Genetics
Bioinformatics
Biostatistics
GWAS
PheWAS
PRS
Rare Variant Analysis
Multi-Omics Integration
QTL Data Analysis
Causal Inference
Machine Learning (ML)
Python
PyTorch
R
Unix/Linux

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 could really set you apart!

Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see how your experience fits the role without wading through unnecessary fluff.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our mission to drive drug discovery with cutting-edge tech!

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 relation to drug discovery or genetic analysis. 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 to enhance genetic discovery.

✨Cross-Functional Collaboration

Be ready to discuss how you've worked with different teams, like ML, biology, and engineering. Share specific examples of how collaboration has led to successful outcomes in your previous roles, as this is key for driving drug discovery decisions.

Statistical Geneticist - ML in Shrewsbury
Searches @ Wenham Carter
Location: Shrewsbury

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