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Data Science and Machine Learning EngineerThe websiteUnited States
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Data Science and Machine Learning Engineer

The website
  • US
    United States
  • US
    United States

Über

.**About the Opportunity****About the Institute for Experiential AI and Northeastern University**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 Engineer 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 and Predrag Radivojac’s group at Khoury College, Northeastern University. There will also be opportunities to work on industry collaborations. Responsibilities will include building an ETL and ML pipelines for multiomics or healthcare data, 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: February 2026 for the Spring 2025 semester with possibilities of renewal. This work will contribute towards drug discovery, protein structure and function prediction and understanding disparities in healthcare.**Qualifications**● MS in Data Science, Machine Learning, Artificial Intelligence, or related fields or currently enrolled in a master’s program.● A minimum of 3-4 years of experience working with ML/AI (TensorFlow/Pytorch) and ETL pipelines.● Proficiency in Python and R. Experienced with Unix and remote computing clusters.● Having experience in wrangling large datasets, building databases and ETL is preferred.● 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.● 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, Harvard Medical School, and University of Virginia.**Key Responsibilities:**The Data Science and Machine Learning Engineer 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 and healthcare 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 (20 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 assistance, wellness & life, retirement- as well as commuting & transportation. Visit
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.This job is for a current or anticipated job vacancy.**Pay Rate:**$40/hourFounded in 1898, Northeastern is a global research university and the recognized leader in experiential lifelong learning. Our approach of integrating real-world experience with education, research, and innovation empowers our students, faculty, alumni, and partners to create worldwide impact.Our global university system provides our community and academic, government, and industry partners with unique opportunities to think locally and act globally. The system—which includes 14 campuses across the U.S., U.K., and Canada, 300,000-plus alumni, and 3,000 partners worldwide—serves as a platform for scaling ideas, talent, and solutions.
The university’s residential campuses for undergraduate and graduate degrees are located in Boston, London, and Oakland, California. Our research and graduate campuses are in the Massachusetts communities of Burlington and Nahant; Arlington, Virginia; Charlotte, North Carolina; Miami; Portland, Maine; Seattle; Silicon Valley, California; Toronto; and Vancouver.Northeastern’s personalized, experiential undergraduate and graduate programs lead to degrees through the doctorate in 10 colleges and schools across our campuses. Learning emphasizes the intersection of data, technology, and human literacies, uniquely preparing graduates for careers of the future and lives of fulfillment and accomplishment.
Our research enterprise, with an R1 Carnegie classification, is solutions oriented and spans the world. Our faculty scholars and students work in teams that cross not just disciplines, but also sectors—aligned around solving today’s highly interconnected global challenges and focused on transformative impact for humankind. #J-18808-Ljbffr
  • United States

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  • English
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