Data Science and Machine Learning Researcher

Northeastern University • Boston, MA

22h

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 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.

Requirements

• 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.
• 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.).
• 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.

Nice To Haves

• A PhD in relevant fields preferred.
• Having published in academic journals is a bonus

Responsibilities

• 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.

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

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees