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Stevens Institute of Technology

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Postdoctoral Associate, Systems Engineering Stevens Institute of Technology in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Annual base salary range: $65,000-$75,000; additional compensation such as stipends is excluded from the stated pay range.

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Country

United States

University

Stevens Institute of Technology

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Keywords

Computer Science
Environmental Science
Systems Engineering
Mechanical Engineering
Electrical Engineering
Industrial Engineering
Sociotechnical Systems
Statistics
Mechatronics
ML

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About this position

Postdoctoral Associate in Systems Engineering at Stevens Institute of Technology joins the Laboratory for Intelligent Integrated Networks of Engineering Systems (LIINES), a research group focused on the sustainable and resilient transformation of intelligent multi-energy engineering systems.

The project centers on assessing the socio-technical potential of transactive energy communities. The postdoctoral researcher will contribute to the design of instrumentation, communication, and actuation systems, including refinement of the overall system, and will also work on the socio-technical energy behavior prediction phase of the project.

This role is strongly interdisciplinary and is intended to involve collaboration with internal and external colleagues. It is well suited to candidates interested in applying machine learning, predictive maintenance, and control algorithms to mechatronic system hardware, especially in a research environment that combines systems engineering with practical, data-driven implementation.

LIINES at Stevens supports research on intelligent multi-energy systems, and this position sits within that broader effort at a private research university in Hoboken, New Jersey.

Funding details

Annual base salary range: $65,000-$75,000; additional compensation such as stipends is excluded from the stated pay range.

What's required

A PhD degree in systems, mechanical, electrical engineering, or a related field is required, along with a strong background in hardware development and practical implementation experience. Applicants should demonstrate competence in one or more of the following: theoretical knowledge of data-driven algorithm development and control theory, practical coding for efficient algorithms using various architectures, independent research applying data-driven algorithms to practical problems, prior publication or project experience in predictive maintenance, and hands-on experience implementing algorithms on resource-constrained mechatronic hardware platforms. Strong organizational and planning skills, proficient writing and presentation skills, and the ability to work in a diverse team, collaborate across research groups, and mentor junior researchers are also expected.

How to apply

Submit an online application through the Workday posting. Attach a cover letter and resume with the application. Direct application questions to [email protected].

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