Teaching-Track Faculty Position in Robotics

Requisition #: A-46079-3

Status: Full Time

Type: Faculty

School: Whiting School of Engineering

Department/Program: Laboratory for Computational Sensing and Robotics

Location City: Baltimore

Location State: MD

Location Zip Code: 21218

Closing Date: Open until filled

General Description

The Laboratory for Computational Sensing and Robotics (LCSR) at the Johns Hopkins University invites applications for a full-time teaching faculty position. The individual selected for this position will be expected to contribute to our educational mission through teaching, curriculum development, and advising and mentoring students, including Robotics MSE students and undergraduate Robotics minors. Johns Hopkins is a private university well known for its commitment to academic excellence and research. Robotics at Johns Hopkins is among the top in the USA in terms of research activities and educational programs. See our web page at http://lcsr.jhu.edu for additional information about research and educational activities. This is a non-tenure-track position, with opportunity for career progression in the non-tenure-track positions of Lecturer, Senior Lecturer, Associate Teaching Professor, and Teaching Professor. The appointment will be in an appropriate academic department within the Whiting School of Engineering.

Qualifications

Qualified candidates at all ranks (Lecturer, Senior Lecturer, Associate Teaching Professor, Teaching Professor) will be considered. The ideal candidate will have earned a Ph.D. in Robotics, Mechanical Engineering, Computer Science, Electrical Engineering, or a closely related field, has a minimum of 5 years of experience in robotics research and development, and will have demonstrated excellence in teaching. It is desired that the candidate has experience and interest in teaching courses in the broad areas of robotics and sensing. Experience in industry or with practically deployed robotic systems is also desirable. We seek candidates with experience teaching and advising students from diverse backgrounds/underrepresented groups. Teaching responsibilities would include graduate and undergraduate courses in topics such as robot control, robot vision, sensor-based navigation, machine learning for robotics, and other closely related topics. Candidates with expertise with physical testbeds and strong ROS programming skills will be preferred.

Application Instructions

Applications should include a cover letter, a curriculum vitae, a statement of teaching philosophy and interests, and a list of references. The application should be submitted electronically via https://apply.interfolio.com/46079. Applicants should arrange for three reference letters to uploaded. Applications will be considered on an ongoing basis until the position is filled, beginning November 30, 2018.

Questions should be directed to Prof. Louis Whitcomb, LCSR Deputy Director, at lcsr-lec-search@jhu.edu.

The LCSR is committed to a diverse and inclusive environment. We seek candidates who through their teaching and service contribute to the diversity and excellence of our academic community. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University's goals of achieving excellent in all areas, we will assess the comprehensive qualifications of each applicant.

To apply for this position, visit: apply.interfolio.com/46079

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.


The successful candidate(s) for this position will be subject to a pre-employment background check.

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