Data Science and Machine Learning Researcher

Data Science and Machine Learning Researcher

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 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 Data Science and Machine Learning Researcher will report

to Ayan Paul, Research Scientist at EAI. There will also be

opportunities to work on industry collaborations. Responsibilities

will include building an ETL and ML pipelines for drug synergy,

write code for data analysis and post-processing data. Training of

models like CNN, RNN, Transformers with some work in classical

machine learning with XGBDTs is expected. Relevant work can lead to

co-author publications and contributions to grant proposals.

Tentative start date: April 2026 for 6 months with

possibilities of renewal. This work will contribute towards drug

synergy research with an industry partner.

Qualifications

• An MS in computer science, data science, computational biology,

or bioinformatics with a heavy focus on machine learning and AI

model training and development by the appointment start date. A PhD

in relevant fields preferred.

• About 5 years of research or work experience in an academic

group. Corporate experience will be considered if it is aligned

with the job role

• A record of outstanding research, as evidenced by software

outputs, and other scholarly measures of impact. Having published

in academic journals is a bonus

• Strong demonstrable background in machine learning. Must have

demonstrable experience in building AI models for drug

synergy.

• Must have 2+ years of experience in computational approaches

and datasets used in drug efficacy and toxicity predictions.

• Must have familiarity with data generated by cell screening

assays, cell painting, and cheminformatics.

• Must have experience in research software development, FAIR

data/open science, life sciences data systems, and analysis of

various kinds of ‘omics data (e.g., metabolomics, proteomics,

genomics, transcriptomics, etc.).

Values & Abilities:

• 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 our industry partners.

Key Responsibilities:

The Data Science and Machine Learning Researcher will be

responsible for a wide variety of data-oriented tasks,

including:

• Building data preprocessing pipelines for ML/AI models

(TensorFlow/Pytorch) for multi-omics, cell screening, and

drug-target affinity data from to achieve state-of-the-art

performance.

• Build ETL pipelines for large datasets

• 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.

Position Type

Non-Student Temporary (40 hrs/week)

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 assi