We use cookies. Find out more about it here. By continuing to browse this site you are agreeing to our use of cookies.
#alert
Back to search results

Assistant Professor - Software and Data Engineering Technology

New Jersey Institute of Technology
United States, New Jersey, Newark
323 Doctor Martin Luther King Junior Boulevard (Show on map)
Dec 03, 2024

Title:
Assistant Professor - Software and Data Engineering Technology

Department:
School of Applied Engr & Tech

Reports To:
Department Chair, School of Applied Engr & Tech

Position Type:
Faculty

Position Summary:
The School of Applied Engineering
and Technology (SAET) of the Newark College of Engineering at the New Jersey Institute
of Technology (NJIT) invites applications for a tenure-track Assistant
Professor position in Software and Data Engineering Technology (SDET). By the
time of appointment, the successful candidate must have earned a Ph.D. (or
equivalent) degree, with a record of pertinent high-quality research in a
related engineering field.

Essential Functions:
- The
successful candidate is expected to teach undergraduate (and occasionally,
graduate) Software and Data Engineering Technology (SDET) courses in the School
of Applied Engineering and Technology (SAET).
- The candidate is expected to
engage in research, advise graduate students (M.S. and Ph.D.), produce
technical publications in peer reviewed journals and conference proceedings,
and obtain grant funding. Areas of research and academic interest of particular
relevance include:
- Applied Informatics/Analytics: With the proliferation of large,
open-source datasets, modern computational software, and novel methods for
unstructured data mining, the field of Informatics is being reimagined. Application
of informatics can include medical, bio, health, energy, and materials
informatics. Candidates whose research includes machine learning will be
strongly considered.
- Artificial Intelligence & Machine Learning: Research areas to
include advanced applications of AI and machine learning, novel AI algorithms
and architectures, and software engineering principles for AI systems
(including topics in scalability, robustness, fairness, and verification).
Areas of applications can include medicine, health sciences, materials,
cybersecurity, cyber-physical systems, human-machine systems, IoT and edge
computing, autonomous systems, energy and the built environment, climate
science, advanced manufacturing, critical infrastructure and supply chain
management, the arts, and life sciences and systems biology.
- Digital Twin and Physics Based
Simulation Software
: Digital Twins are becoming an important technology
applied to several industry areas including product design, manufacturing, and
construction. Research areas include advanced applications of physics based
simulation software, sensor simulation, robotics simulation, human-autonomous
agent interaction, and autonomous vehicle simulation. Areas of applications can
include automotive, construction, aerospace, robotics, manufacturing, product
development, health and medicine, and supply chain management.

Prerequisite Qualifications:
-By the time of appointment,
successful candidates must have earned a Ph.D. (or equivalent) degree, with a
record of pertinent high- quality research in a related engineering field.
- At the
university's discretion, the education and experience prerequisites may be
exempted where the candidate can demonstrate to the satisfaction of the
university, an equivalent combination of education and experience specifically
preparing the candidate for success in the position.

Preferred Qualifications:
Applicable industrial experience
and prior teaching experience are highly desirable.

Bargaining Unit:
PSA

FLSA:
Exempt
Full-Time

Special Instructions to
Applicants:
Rank and salary will be commensurate with qualifications and
experience. Applications must include a curriculum vitae, cover letter, research
and teaching statements, and list of three (3) professional references.
Questions may be directed to the department interim chairperson, Dr. Samuel
Lieber at samuel.lieber@njit.edu.

Applied = 0

(web-86f5d9bb6b-jk6zr)