Internship In Computational Biology: Cvrm Genetics

Roche

Strong coding experience in r and python
Proficiency with plink bcftools or regenie
Foundational understanding of gwas and pgs
The role focuses on building automated Polygenic Risk Score workflows to investigate the genetic architecture of chronic kidney disease and metabolic dysfunction

Job Summary

  • The role focuses on building automated Polygenic Risk Score workflows to investigate the genetic architecture of chronic kidney disease and metabolic dysfunction.
  • Candidates will work with large-scale genomic, proteomics, and electronic health record datasets to drive target discovery for novel therapeutics.
  • Roche offers a culture that encourages personal expression, open dialogue, and genuine connections where every voice matters in preventing and curing diseases.

Matching Summary

The role focuses on building automated Polygenic Risk Score workflows to investigate the genetic architecture of chronic kidney disease and metabolic dysfunction.

Skills & Requirements

Must-have

  • Strong coding experience in R and Python
  • Proficiency with Plink BCFtools or REGENIE
  • Foundational understanding of GWAS and PGS
  • Expertise in quantitative statistics and data modeling
  • Experience with large biobanks like UK Biobank

Nice-to-have

  • Familiarity with Docker and Snakemake workflows
  • Interest in applying AI tools to biological methodologies
  • Creative problem-solving skills in ambiguous environments
  • Collaborative mindset within multidisciplinary teams
  • Experience with proteomics data analysis

Key Requirements

  • Master's degree in Systems Biology or related discipline
  • Recent graduate status (less than one year post-graduation)
  • Mandatory internship confirmation for non-EU/EFTA citizens if applicable

Work Rights

Non-EU/EFTA citizens must attach university confirmation for mandatory internships; otherwise not specified

Tailored Resume

Cover Letter