Clinical Trials & Experimentation Research Intern (Start ASAP)

Job Description

The CSX Data R&D group and the Machine Learning and Statistics group at Microsoft Research New England are hiring an intern to work alongside leading researchers and engineers to study fairness in randomized control trials (RCTs).

Randomized controlled trials (RCTs) are an integral part of experimentation, whether via clinical trials to evaluate medical treatments or via A/B testing to evaluate online interventions. 

Responsibilities

• The research intern will analyze the performance of different stopping methods on both simulated and Microsoft’s experimentation data -- considering both observed and unobserved subgroup heterogeneity.  
• The research intern will then develop better-stopping rules for heterogeneous data, focusing on fairness with respect to underserved and marginalized communities, and will apply these methods internally with the goal of integration with Microsoft’s standard A/B testing practices. 
• Interns put inquiry and theory into practice alongside fellow doctoral candidates and some of the world’s best researchers, interns learn, collaborate, and network for life. Interns not only advance their own careers but also contribute to exciting research and development strides.
• During the 12-week internship, students are paired with mentors and expected to collaborate with other interns and researchers, present findings, and contribute to the vibrant life of the community.

Required Qualifications

• Must be currently enrolled in a PhD program in Statistics, Biostatistics, Computer Science, or a related STEM field.  
• Participation in the Research Internship Program requires that you are physically located in the United States or Canada for the duration of the internship.
• You’ll need to submit a minimum of two reference letters for this position. After you submit your application, a request for letters may be sent to your list of references on your behalf. 

Preferred Qualifications

• Authored at least one conference or journal publication or preprint in statistics, machine learning, or a related field.