Teaching-Track Faculty Position in Robotics

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 https://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 Senior Lecturer, Associate Teaching Professor, and Teaching Professor.

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.

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 beginning November 30, 2018.

Questions should be directed to Prof. Greg Chirikjian, 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.

Navigation and Locomotor Control in Augmented Reality
PI’s: Noah Cowan & James Knierim, Johns Hopkins University

The Cowan and Knierim laboratories have multiple funded projects from NIH and DOD investigating the neural computations that underlie navigation in the physical world. We are using a novel augmented reality apparatus and multi-electrode neural recordings of place cells, grid cells, head direction cells, and other cell types of the hippocampus and related brain regions to reverse engineer the interplay between navigation and locomotor control in freely behaving animals (see https://limbs.lcsr.jhu.edu/ and http://sites.krieger.jhu.edu/knierim-lab/). We are seeking dynamic and ambitious postdoctoral candidates who are highly skilled in experimental research in potentially diverse areas (e.g. biomechanics, neuroscience, robotics, control systems, or physics). The ideal candidate will also have a strong computational background (e.g. dynamical systems, information theory, control theory) and/or strong data analysis skills (e.g. statistical methods, data mining, Bayesian filtering, spectral analysis, machine learning).

Qualifications: PhD in Engineering, Neuroscience, Biology, Physics, Computer Science, or related fields. Strong computational and experimental background a must.

How to apply: Interested applicants should send a single PDF including a brief (1 page) cover letter, CV (no more than 4 pages, including a list of 3 references), and up to two papers to ncowan@jhu.edu