748 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Northeastern University in United States
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About the Opportunity About Northeastern: Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned
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models. The role also requires significant experience in classical machine learning methods such as decision trees, gradient boosting machines, and both shallow and deep learning networks. A demonstrated
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 28-Dec-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Computer/Information Sciences
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harnessing emerging technologies to advance human potential and solve the challenges of the future. Powered by experience-driven teaching, learning and research, CAMD believes that the fields of design
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conducive to the social, personal, and academic success of first-year students during the program. On-site staff members focus on creating positive and valuable experiential learning opportunities for NYC
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About the Opportunity About Northeastern Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned
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), electrophysiology, genotyping, brain stimulation (tES, TMS), computational modeling and/or machine learning. For all our projects, we seek post-doctoral researchers who aim to take leading roles in projects
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research, teaching, and engagement missions, the college collaborates across the university, the Northeastern network, and partners around the globe. Responsibilities: Teach European, World, or American
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About the Opportunity The College of Science at Northeastern University is looking for part-time lecturers to teach a graduate course, called EESC-6500 Pathways to Professional Success , for Fall
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collaborate with academic and industry partners of EAI. Minimum Qualifications: An MS in computer science with a heavy focus on machine learning and LLM-RAG construction and development by the appointment start