Research Associate - Machine Learning and Artificial Intelligence

About the Opportunity

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 Dr. Usama Fayyad, 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 and Artificial Intelligence Research Associate will report to Ayan Paul, Research Scientist at EAI and collaborate with Scientists and Clinicians from Peter Castaldi’s group at the Harvard Medical School, John Platig’s Network Biology group at University of Virginia and Jennifer Dy’s Machine Learning group at ECE, Northeastern University. Responsibilities will include building an ML/AI pipelines for multiomics data, write code for data analysis and post-processing data using standard Bioinformatics libraries in python and R. Focus will be on sequence models like CNN, RNN, Transformers with some work in classical machine learning with XGBDTs. In addition, there will be opportunities for building GNNs for graph data and work with explainability measures in XAI. Relevant work can lead to co-author publications and contributions to grant proposals. Tentative start date: February 2025 for the Spring 2025 semester with possibilities of renewal. This work will contribute towards the understanding of genetic origins of complex diseases like Chronic Obstructive Pulmonary Disease and cutting-edge machine learning based methodologies for regulation of mRNA splicing.

Qualifications

• BS in Computer Science, Physics, Mathematics or related fields or currently enrolled in a bachelor’s program.
• A minimum of 1 year of experience working with ML/AI (TensorFlow/Pytorch) and ETL pipelines.
• Experience with CNN, RNN, graph leaning, and/or transformers (hands on work)
• 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.
• Experience with AWS is a plus but not required

Values & Abilities:

• Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders from various academic backgrounds.
• 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, Harvard Medical School, and University of Virginia. 

Key Responsibilities:

The ML/AI Research Associate will be responsible for a wide variety of data-oriented tasks, including:

• Building ML/AI models (TensorFlow/Pytorch) to achieve state-of-the-art performance.
• Develop explanability methods for XAI in the sequence and graph learning domains.
• 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.

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer. 

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.

Position Type

Temporary

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.  

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.