194 phd-computer-science-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at University of Texas at Arlington
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
Qualifications Bachelor’s degree in data analytics, business, computer science, education or a related field. At least two (2) years of professional experience in data analysis, reporting, or institutional
-
degree in one of the following areas: Computer Technology, Information or Computer Systems. Five (5) years of hands-on systems analysis, software development, design, and application development experience
-
) years of an equivalent combination of education and related experience. Preferred Qualifications Master’s degree or PhD from an accredited college or university in water resources, engineering, natural
-
Science Foundation. RTG themes include modeling in cancer biology, computational neuroscience, and mathematical epidemiology. Mathematical techniques include qualitative and numerical analysis
-
instruction within the College of Nursing and Health Innovation. 2. Reports directly to the NNP Program Director. 3. Maintains academic standards as established by the university, CONHI and Department
-
skills will vary but encompass account access, email, network connectivity, software, academic technology, computing endpoint devices, printers, and other technology peripherals. The annual salary
-
; undergraduate and/or graduate student mentorship. Required Qualifications PhD in Social Work, Psychology, Public Health or related healthcare field. Prior scholarly work in the area of health policy and services
-
the Department. Required Qualifications Possess a PhD, DBA or equivalent in Finance (or closely related field) at the time of joining the faculty or be ABD and close to finishing the PhD. All candidates should
-
Position Information Posting Number F00444P Position Title Assistant Professor Department Electrical Engineering Location Arlington Job Family Faculty Position Status Full-time Rank Tenure-track
-
aerospace engineering, and computational modeling to study the structural behavior of buildings under wind loads and drive advancements in urban planning and hazard mitigation strategies. This initiative will