Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
and technical information about the Technical Assistance for Water Loss Control (TAWLC) program, water conservation, leak detection, efficiency measures, financial assistance, and emerging issues
-
on assigned audits. Develops audit objectives, scope and work program. Performs fieldwork activities and conducts client interviews. Performs all audit work in accordance with The Institute of Internal Auditors
-
to amplify research standing and position UTA as a leader in key scholarly areas; more details are available at https://www.uta.edu/administration/president/strategic-plan/rise100 . The successful candidate
-
program in the strategic area of resilient and sustainable cementitious structural materials for the infrastructure. These positions shall focus in one or more of the following areas of interest (but not
-
charter, perform stakeholder analysis, identify project approach, and plan and facilitate project kickoff. Drive the project planning stage and facilitate team collaboration to identify requirements and
-
understanding of all applicable federal, state, and University policies and procedures. Keep informed of relevant academic programs and support services such as counseling and tutoring within a College and
-
which require a thorough understanding of the functions, program and policies of the University. Assists in the management of administrative staff services and in developing and implementing internal
-
assist with the evaluation, review, selection, adaptation, and modification of standards, techniques, procedures, and criteria for public water systems design for the Plan and Technical Review Section
-
; ability to learn TCEQ databases. Solid working knowledge of TCEQ and Environmental Protection Agency rules, regulations, and procedures related to publicly owned treatment works and pretreatment programs
-
. Preferred Qualifications Experience with: C/C++, Python, MATLAB, ROS 1 and 2, OpenCV, Unity, GPU programming, linear and nonlinear control theory, supervised, unsupervised and reinforcement learning, Torch