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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

21Open Positions

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Internship in Biostatistics for Master and PhD Students

Roche
Found 4 days ago
Location
Basel, Switzerland
Duration (Months)
4.5 Months
Time
Full-time
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
4 days ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • Statistics
  • Biostatistics
  • R programming language

Soft Skills

  • Highly organized
  • eager to learn
  • passionate about connecting statistical theory with real-world drug development challenges

Job Description

As strategic partners in drug development, we apply our drug development and statistical expertise to the design and analysis of clinical development plans, clinical studies, and non-clinical experiments. We are seeking a motivated intern to join the Early Development Biometrics (EDB) team in Basel. You will develop a statistical framework to evaluate biomarkers as potential surrogate endpoints for use in early-phase clinical trials. In particular, you will explore the utility of causal mediation analysis in assessing the proportion of the treatment effect mediated by candidate surrogates. Evaluate various causal mediation methods to identify the most robust techniques for surrogate validation. Explore historical Roche trial data across diverse therapeutic areas: Ulcerative Colitis, Huntington’s Disease, and Alzheimer’s Disease etc. Conduct extensive simulation studies to stress-test causal mediation methods under different conditions. Develop reusable software/code to facilitate uptake of these methods for broader use within the biometrics team. Get familiar with existing methods through targeted literature review. Consolidate research findings and simulation results into clear presentations.

Requirements

  • enrolled in a Master or PhD program in Statistics or a related field, or you graduated from your Master's studies within 12 months before the internship start date
  • strong theoretical foundation in statistics
  • experience in applied statistics
  • proficiency in the R programming language
  • Highly organized
  • eager to learn
  • passionate about connecting statistical theory with real-world drug development challenges
  • Fluency in English

Related Field

  • AI & Machine Learning

Related Subfield

  • AI Research

Languages

  • English

Nice to Haves

  • causal inference
  • mediation analysis
▶Apply Now

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