Oncology Data Science & Analytics (Virtual Assignment)
Type of Student: PhD candidates in statistics, biostatistics, computer science, data science, mathematics
Deadline: March 15, 2021
Oncology Data Science & Analytics department is an integral part of the Oncology R&D organization. Embracing diversity and inclusion, we work to bring the best analytics to the right data, helping to make the right quantitative decisions, and advancing drug development with innovation in Statistics and Data Science.
In this 12-week summer program (beginning May/June), you can choose to work with mentors from ML/AI, RWE or Statistical Innovation groups on broad analytical topics such as novel ML/AI algorithm development, innovative clinical trial design and simulation, missing data imputation, RWD-based synthetic cohort building, propensity score matching, health economics modeling, and health technology assessment. You will present project learnings to the department and start preparing a draft manuscript for publication at the conclusion of the internship. It is a great opportunity for you to apply cutting-edge methodology to solve real-world problems, and to generate future research ideas.
Requirements:
Students must also meet the following eligibility criteria:
- Enrollment in a graduate-level curriculum leading to a PhD in statistics, biostatistics, data science, computer science, epidemiology, public health or mathematics;
- Completion of at least two full years of graduate study prior to the start of the internship;
- Must be in good academic standing within graduate program and at university overall with an accumulated GPA of ≥ 3.0;
- Good written and oral communication skills;
- Demonstrate proficiency in statistical programming using SAS and/or R, preferably R shiny;
- Authorization to work in the US.