Log In
Sign Up
SUMMARY:
Lawrence Technological University in Southfield, Michigan, is seeking to hire an Assistant or Associate
Professor in areas of machine learning, autonomous robotics, and cybersecurity. Applications are sought generally across the three areas,
but specific topics of interest include neural network design, fog intelligence, learning from demonstration, robot perception, machine
learning security, and secure autonomy.
JOB DUTIES:
The successful candidate is required to teach graduate and
undergraduate courses as assigned, mentor undergraduate and graduate students, and establish a strong, externally-funded research program in
his/her area of expertise. In addition, the successful candidate will also contribute to the department, college, and university functions.
The successful candidate is expected to work in a highly interdisciplinary and collaborative environment across departments and colleges
while maintaining the highest standards in the classroom. In addition, LTU has recently created a new PhD program in Computer Science and
the successful candidate will be expected to apply and receive funding to help support PhD students. Other duties may be
assigned.
EDUCATION and/or EXPERIENCE:
Earned doctorate from an accredited university in computer science, or a
closely related field. Postdoctoral experience is highly desirable. Demonstrable interest in teaching and mentoring graduate and
undergraduate students. Interest in establishing a robust and externally-funded research program.
Expertise in your area of focus
must be shown by a strong publication record. Interest in programming, novel computational approaches, and/or demonstrated ability to work
in interdisciplinary, collaborative teams a plus.
Interested applicants must send as a single PDF file: a cover letter describing
interest and qualifications for the position, a complete and updated CV, a statement of teaching philosophy, a statement of research
interests and goals, a list of five professional references, and reprints of three representative, peer reviewed publications to [email protected]. Please indicate the rank for which you are applying.
Salary will be commensurate with experience; the start date is negotiable but cannot be later than September 2024.
