About this role
Based in Boston, United States, Massachusetts Institute of Technology is hiring for a Postdoctoral Researcher – Scientific Machine Learning for Next-Generation QSP Models position, working on-site. It is an Artificial Intelligence & Data role, and the posting is filed under that category. The posting is for an office role in Boston, with the team based there. Experience at mid-level fits here, and the posting is written with that in mind. The rest — requirements, and how to apply — is in the employer's description below.
Your Career Hunter matched this listing against the employer's careers page on Nov 13, 2026.
Job Overview
Job description provided by Massachusetts Institute of Technology.
MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) is seeking a highly motivated postdoctoral researcher for a collaborative project with GSK.
The project integrates Scientific Machine Learning (SciML) with Quantitative Systems Pharmacology (QSP) models to develop next-generation high-fidelity predictive models.
The researcher will develop and train advanced emulator models using stiff ODE QSP systems, with applications to HIV, HBV, and other disease models.
Work will also explore automated discovery of missing elements of models using universal differential equations, and assess whether QSP model emulation with available data beats traditional approaches.
The fellow will build predictive ML models using preclinical and clinical training data and create SciML models combining QSP/QST frameworks with clinical datasets.
Novel datasets such as omics data will be integrated with traditional QSP approaches, and the fellow will develop open source Julia software packages for the research community.
The role includes collaborating closely with GSK researchers through regular meetings, publishing findings in high-impact journals, and presenting at conferences.
Applicants need a PhD in computer science, applied mathematics, computational biology, bioengineering, or a related field, with strong programming experience in Julia or a willingness to learn.
Demonstrated major contributions to open source libraries, experience with differential equations, and a background in machine learning and scientific computing are required.
This is a two-year position at MIT CSAIL in Cambridge, Massachusetts, with applications open until filled. Applicants should submit a cover letter, CV with publication list, three references, and a brief research statement to Dr. Chris Rackauckas at crackauc@mit.edu.