• Assistant/Associate/Full Professor, tenure or tenure-track position with expertise in Intelligent, Secure, Autonomous and High Performance Systems

    The Department of Electrical and Computer Engineering at Northeastern University invites applications for multiple open positions at all levels. We seek exceptional candidates addressing problems in cybersecurity, big data computing, all areas of robotics, Internet-of-Things (IoT) systems, and high performance systems, with expertise broadly in one or more of the following areas:

    • secure hardware and software systems/devices,
    • embedded systems and sensing, power-aware computing and system-on-chip,
    • robotics, including vision, learning, actuation and field robotics
    • neuro-computing/engineering, brain interfacing and health monitoring,
    • big data, computation, machine learning, and visualization, 
    • high performance systems and architectures

    Outstanding candidates at all levels will be considered.

    Candidates should be committed to fostering diverse and inclusive environments as well as to promoting experiential learning, which are central to a Northeastern University education.

  • Assistant/Associate/Full Teaching Professor, non-tenure-track position in Electrical & Computer Engineering with a focus on Data Science

    Northeastern University’s Department of Electrical & Computer Engineering seeks outstanding candidates for the position of Assistant/Associate/Full Teaching Professor with a focus on Data Science. This is a full-time, benefits-eligible, non-tenure-track position. Appointments are made on an annual 8-month basis, with salary commensurate with experience. The position of Assistant Teaching Professor entails educational interaction with students in roles including, but not limited to, traditional instruction (lecture courses, lab courses), project team advising, and student organization advising. The main responsibility of this position is teaching classes that make up the master’s program in Data Science, such as classes on algorithm design, data processing, machine learning, data mining and data visualization. The annual teaching course load is six courses, with the potential for teaching more than one section of a course in the same semester, over Fall and Spring semesters. Courses may be at both the undergraduate and graduate levels.

    Teaching professors are also encouraged to pursue scholarly research on both educational and pedagogical topics as well as in their technical area of expertise, and have the opportunity to supervise graduate students.