Summer or Fall 2026 Co-op_Intern - RNA Machine Learning - Vaccine

Job Title: Summer or Fall 2026 Co-op_Intern - RNA Machine Learning - Vaccine

Location: Waltham, MA

About the Job

As an RNA Machine Learning Co-op, you will participate in a 6-month project in the areas of cheminformatics, bioinformatics, computational biology, and machine learning to the task of developing and implementing first-in-class and best-in-class computational solutions and models for screening, optimizing and evaluating RNA molecules for mRNA-based vaccines and therapeutics as part of the Data and Computational Science team in the mRNA CoE.

This team brings end-to-end data integration and advanced analytics (pre-clinical, biomarkers, process development, CMC, clinical) in the mRNA CoE. Deploying and exploiting digital solutions (AI/machine learning, data, analytics) to integrate the full data value chain, extracting actionable information for a move to a full data driven strategy and decision-making process, to increase probability of success and to accelerate mRNA vaccines and therapeutics development and launch.

We are an innovative global healthcare company that helps the world stay ahead of infectious diseases by delivering more than 500 million vaccine doses a year. Across different countries, our talented teams are exploring new technologies to protect people and promote healthy communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.

Main Responsibilities:

• Collaborate with group experts in the development and execution of the scientific strategy and technical solutions to develop best-in-class mRNA vaccines and therapeutics

• Execute development of a project to deliver data and computational solutions for the integration of chemical, structural, and biological data to support data analytics and visualization

• Design, develop, and validate robust analytical and machine learning approaches to support in silico characterization, screening, optimization, and analysis of mRNA molecules

• Collaborate internally to develop scientific hypotheses and drive new scientific insights based on computational frameworks

• Develop, deploy, and assess the results of at-scale models at varying levels of model granularity encompassing heterogeneous preclinical and clinical data

• Employ machine learning methods such as deep learning, neural networks, reinforcement learning, graphical, and generative models to deconvolve high dimensional experimental and in silico modeling results

• Maintain a well-documented, reusable codebase, and traceable model history

• Maintain awareness of latest developments in relevant fields, evaluate and apply as warranted

• Demonstrate good software engineering practices

• Proactively identify, assess, and internalize emerging technologies and methods

About you
Basic Qualifications:

• Currently enrolled and pursuing a master’s degree or, PhD in Bioinformatics, Computational Biology, Computer science, or related quantitative disciplines at an accredited college or university with the expectation that you will complete your current degree by the Spring of 2028

• Must be able to relocate to the office location and work 40hrs/week, Monday-Friday, for the full duration of the co-op/internship

• Must be permanently authorized to work in the U.S. and not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future. Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship 

• Experience in scientific computing (e.g., python, R)

• Experience in computational and statistical analysis, quantitative modeling, and machine learning algorithms

Preferred Qualifications:

• Practical experience proposing, prototyping, and deploying novel algorithms; developing and val