Description

In this internship, you will dive into preclinical neuroscience research by leveraging historical data to create virtual control groups. Your work will involve statistical analysis, collaboration with experts, and sharing findings with the broader research community.

Requirements

• •Enrollment in a PhD in Mathematics, Statistics, or scientific field with strong statistics focus
• •Expertise in data wrangling, quantitative methods, and statistical modeling
• •High level of statistical programming proficiency
• •Practical experience using programming software (R or Python)
• •Experience in cross-disciplinary problem solving
• •Understanding of scientific experimentation concepts
• •Curious mindset and can-do attitude
• •Ability to deliver high quality results with urgency
• •Excellent interpersonal and communication skills
• •Openness to seek, receive, and give feedback
• •Ability to synthesize complex findings into clear guidelines

Tasks

• •Systematically review methodologies for Virtual Control Group generation
• •Conduct exploratory analysis of a large historical data repository
• •Define necessary matching criteria for VCG creation
• •Explore and apply advanced statistical approaches for VCG generation
• •Validate VCG generation methods using R or Python
• •Utilize a high-performance computational cluster for analysis
• •Collaborate with interdisciplinary experts across Roche
• •Communicate progress and results during internal meetings
• •Synthesize scientific findings for the department and external community
• •Develop preliminary guidelines for VCG generation
• •Contribute to drafting a manuscript for publication

Tools & Technologies