629 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Dip" uni jobs at Northeastern University in United States
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About the Opportunity The Department of Bioengineering, College of Engineering, invites applications for the Part-Time Lecturer position for teaching selected undergraduate or graduate courses
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institute that conducts cutting-edge applied R&D – is seeking a highly motivated and enthusiastic Principle/Senior Research & Development (R&D) Engineer with expertise in Embedded Software Engineering. The
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, architectural history, technology, or project case studies; as well as other undergraduate and graduate courses depending on expertise, enrollment, funding, and departmental needs. Qualifications: Master of
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overtime, and believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities
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teaching individuals and institutions the skills needed to design and implement innovative and equitable solutions to our hardest problems and is seeking a web developer who will be responsible
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are particularly interested in candidates qualified for a joint appointment between the School of Architecture and the Department of Mechanical and Industrial Engineering in the College of Engineering. We seek
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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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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 18-Mar-26 Location: Seattle, Washington Type: Part-time Categories: Academic/Faculty Engineering Internal Number
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About the Opportunity The Department of Mechanical & Industrial Engineering (MIE) at Northeastern University is seeking outstanding individuals to fill a full-time non-tenure-track faculty position
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About the Opportunity JOB SUMMARY The Sr Machine Learning (ML) Engineer applies expertise in deploying and scaling AI pipelines across at least one major cloud platform (AWS, GCP, or Azure