- Type
- Full-time
- Education
- PhD
- Closing date
- Today
- Source
- Vincere
Description
Exciting opportunity for someone who can turn massive genetic datasets into real therapeutic insights. If you want to own the work end-to-end and see it matter, keep reading.
Role:
- Process and analyse large-scale multi-omics and population-scale genetic data (GWAS summary stats, molecular QTLs, WGS/WES).
- Run post-GWAS integration — colocalization, Mendelian Randomization, transcriptomic and proteomic data — to identify high-confidence drug targets.
- Build and apply ML/deep learning models tailored for functional genomics.
- Design and maintain production-grade, automated analysis pipelines.
Requirements:
- PhD or MSc in Statistical Genetics, Computational Biology or Bioinformatics
- Hands-on experience with genetic association studies and multi-omics integration.
- Strong coding skills and a commitment to clean, automated pipelines.
- Experience with deep learning architectures for genomics applications is a bonus
Interested candidates, please submit your profile to [email protected] for review. We will be in touch for initial discussion upon being shortlisted
EA Licence: 17S8795 | EAP: R1108333
Skills
Deep Learning
