95 structures-"https:" "https:" "https:" "https:" "https:" positions at Northeastern University in United States
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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protected by applicable law. Pay Range: The per credit rate is $1,529. To apply, visit https://northeastern.wd1.myworkdayjobs.com/en-US/careers/job/Portland-ME/Part-Time-Lecturer---Construction-Management
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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
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About the Opportunity Job Summary The Workday System Analyst, Data Modeling & Configuration is responsible to maintain and optimize Workday foundational data structures (supervisory orgs, job
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(NUBIC), which houses our Siemens Prisma 3T MRI. CBH harnesses neuroimaging, behavioral, and computational studies to understand how lifestyle choices and behaviors influence brain activity, structure
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transition from legacy data structures to a modern, scalable, AI‑ready data architecture. This role conducts deep assessments of existing systems—including Banner, Workday, Salesforce, ServiceNow, Snowflake
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properties. Direct and oversee bioassay development, screening, and hit validation efforts. Manage compound isolation, purification, and structure elucidation workflows in collaboration with analytical and
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. Multidisciplinary collaboration is now indispensable to transformative research and learning, and in this context, the Executive Director will provide structure and strategy to teams who will be integral
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for major renovations, new construction, and campus expansions across domestic and international sites. Represent public safety interests in design and construction meetings with Facilities, Design and
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(DfMA) and industrialized/offsite construction; robotics and human–robot collaboration for fabrication and assembly; AI, data, and digital twins for the built environment; circular, low‑carbon, and