Have you always wanted to work on a real-world problem in pharmaceutical R&D? The Novartis Quantitative Science Academia-to-Industry Hackathon is a two-week event to give graduate students and postdocs hands-on training and on-the-job experience focusing on real-world problems in pharmaceutical drug development. The program is targeted to graduate students and postdocs in the quantitative sciences (e.g. Bioinformatics, Engineering, Mathematics, Pharmacometrics, Physics, Statistics, Systems Pharmacology).
About the Hackathon
The Hackathon is a yearly event which will take place on our site in Cambridge, MA during the month of August. The Hackathon includes a three-day crash course on fundamentals in Translational Quantitative Sciences including basic pharmacokinetics and pharmacodynamics (PKPD) and population PKPD using the open-source R-based nonlinear mixed effect modeling software nlmixr.
Following the course, participants will work in project teams on real-world, open-ended problems in collaboration with Novartis scientists working across the R&D spectrum.
The teams will present their final results at the “Quantitative Sciences in Drug Development Conference” sponsored by Novartis, which will be held on the last day of the Hackathon.
Timing and logistics
The Hackathon is a two-week program. It is scheduled for August 10 – 21, 2020. Daily programming will take place from 9:00 AM to 5:00 PM EDT.
The Hackathon will take place at the Novartis Campus, in Cambridge, MA. Novartis will not provide any travel or accommodation reimbursement for this event. Novartis will provide breakfast and lunch for the duration of the engagement.
How to apply
Application for 2020 is not yet open. Please stay tuned until we announce later in 2019 that the application process has opened. Applicants must be current master students, graduate students or postdoctoral fellows. Once the application process has opened, the following materials will be accepted at [email protected]:
One page statement of reason for participation, career goals, and relevant experience
Resume or CV
Letter of support from advisor, director of graduate studies, or department chair (Optional)