Research Associate – Machine Learning and Artificial Intelligence

Overview

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.

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. Visit https://hr.northeastern.edu/benefits/
for more information.

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.

To apply, visit https://northeastern.wd1.myworkdayjobs.com/en-US/careers/job/Boston-MA-Main-Campus/Research-Associate—Machine-Learning-and-Artificial-Intelligence_R131878

jeid-de19d07e1525f9459726e2bb3af6218b

Company:

Northeastern University

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Academia, Data Analysis, Machine Learning, NLP, United States