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Postdoctoral Researcher (PIER - Trustworthy Artificial Intelligence)-1

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Prairie View A&M University

100 University Dr, Prairie View, TX 77446, USA

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Postdoctoral Researcher (PIER - Trustworthy Artificial Intelligence)-1

Job Title

Postdoctoral Researcher (PIER - Trustworthy Artificial Intelligence)-1

Agency
Prairie View A&M University

Department
Electrical Engineering

Proposed Minimum Salary
Commensurate

Job Location
Prairie View, Texas

Job Type
Staff

Job Description

The Postdoctoral Researcher will conduct research in Trustworthy AI with a focus on optimizing cyber-physical systems. The position integrates research, teaching, and service to support Prairie View A&M University's leadership in advancing research and education in Trustworthy AI. The Postdoctoral Researcher will engage in interdisciplinary collaborations with researchers from the College of Arts and Sciences and the College of Juvenile Justice, participate in professional development workshops, and contribute to grant development activities.

The appointment is a one-year, full-time position in residence at Prairie View A&M University. The university retains the option to renew the appointment for a second year based on performance, research progress, and availability of funding. The maximum term is two years.

This position is funded by restricted funds or a grant. Continued employment is contingent upon the renewal of restricted or grant funds.

Please Note: This postdoctoral position may serve as a potential pathway to a tenure-track position after one year, contingent upon performance and institutional need.

The salary is determined in accordance with the University's compensation structure and will be commensurate with the candidates' education and experience, within the assigned salary range for this position.

Responsibilities:

  • Conduct independent and collaborative research addressing Trustworthy AI for improving cyber-physical systems.
  • Lead experiments, simulations, and testbed prototyping activities.
  • Engage in interdisciplinary research with faculty from the College of Arts and Sciences and the College of Juvenile Justice.
  • Publish research findings in top-tier academic venues.
  • Teach one course per semester within the College of Engineering or collaborating colleges.
  • Mentor undergraduate and graduate students engaged in research.
  • Participate in professional development workshops, write grant proposals, and contribute to other grant development activities. Perform other duties as assigned.

Required Education & Experience:

  • Doctor of Philosophy (PhD) in Electrical Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field (earned within the past three years). Candidates that have finished all required coursework and exams but have not completed or defended their final dissertation may be considered but must have a conferred Doctoral Degree at the time of appointment.
  • Research experience in Trustworthy AI with applications to cyber-physical systems.
  • Evidence of scholarly productivity (e.g., strong publication record, software tools developed, testbeds designed, datasets created).

Preferred Qualifications:

  • Teaching experience in related fields.
  • Experience mentoring students in research.

Required Attachments:

Resume or Curriculum Vitae
Cover Letter

Application Submission Guidelines:
All applicants are required to apply via our Career Site on or before the closing date indicated on the job posting. ... Please contact the Office of Human Resource on or before the closing date indicated above at 936-261-1730 or jobs@pvamu.edu should you need assistance with the online application process.

Background Check Requirements:
All positions are security-sensitive. ...

To apply, visit https://tamus.wd1.myworkdayjobs.com/en-US/PVAMU_External/job/Prairie-View-TX/Postdoctoral-Researcher--PIER---Trustworthy-Artificial-Intelligence--1_R-089887-1?workerSubType=0e1cd8ed3502012ddf607157e74b7d04&workerSubType=0e1cd8ed35020103f9b47257e74b7f04&workerSubType=0e1cd8ed350201da3af87057e74b7c04&workerSubType=0e1cd8ed35020108df607157e74b7e04

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