Machine Learning Researcher, Epidemiology

Northeastern University • Boston, MA

7d

About The Position

About the Opportunity About the Institute for Experiential AI and Northeastern University Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We have launched a pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof Alan Mislove, the Institute for Experiential AI is built around the challenges and opportunities made possible by human-machine collaboration. The Institute provides a framework to design, implement, and scale AI-driven technologies in ways that make a true difference to society. Our ability to respond to the opportunities afforded to society will depend on training and building a workforce that is AI-capable and prosperous. Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned experiential approach empowers our students, faculty, alumni, and partners to create impact far beyond the confines of discipline, degree, and campus. The Culture Here at the Institute for Experiential AI (EAI) we are committed to the highest standards in all that we do. Working at the EAI offers opportunities, an environment, and a culture that just aren’t found together anywhere else. This is the right place for you if you’re curious, motivated by the future of technology, and want to be part of a unique and diverse community that works on high-impact research, educational, business, and societal problems. Position Summary The Machine Learning Researcher - Epidemiology will report to Ayan Paul, Research Scientist at EAI and collaborate with researchers and faculty at NetSci and NU London. Responsibilities will literature review and validation of mathematical frameworks for epidemiology with some coding of simulations. Tentative start date: February 2026. This work will contribute towards the understanding of disease progression and building reinforcement learning frameworks for epidemiology that can be applied at the population level and also at the molecular and cellular level for biological applications.

Requirements

• Graduated with an MS degree in Computer Science, Mathematics, Physics, or related fields.
• A good knowledge of applied mathematics and reinforcement learning with an interest to learn domain knowledge in epidemiology.
• An ability to write clean and well-documented code and work with GitHub repositories.
• Excellent organizational skills including attention to detail and multitasking.
• An ability to troubleshoot and problem-solve in response to challenges, especially, in an unfamiliar domain.
• Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders from various academic backgrounds.
• Respect for diversity and the importance of interdisciplinary teams.
• Self-starter and innovative thinker and a team-player who can collaborate effectively in a university setting.
• Open-minded, assertive, and professional when collaborating and working within our team and with other groups within Northeastern University and any collaborating institutions.

Responsibilities

• Literature review of the current state of the art in epidemiological modeling.
• Develop simulation and network-based methods for epidemiological modeling.
• Develop reinforcement learning models for decision-making during epidemic outbreaks.
• Documenting the entire process and all the codes generated and maintaining structured and regular commits in a Github repository.
• Write reports/prepare slide decks describing work performed.
• Contribute to scientific manuscripts and grant proposals where appropriate.

Benefits

• Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation.

What This Job Offers

• Number of Employees: 5,001-10,000 employees