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Job ID: 263779

Assistant/Associate Professor
Alcorn State University

The incumbent teaches Advanced Technologies courses, contributing to the optimum achievement of the instructional, research, public service, student recruitment, retention and progression, goals and objectives of the department, division and university.

  Knowledge Skills and Abilities

Advanced computer knowledge
Demonstrated integrity, loyalty and time management skills
Strong analytical, observational, and problem-skills skills
Excellent research, writing and interpersonal skills
Excellent communication and collaborative skills
Passion for teaching and engaging with students
Skilled in mentoring students
Ability to work well with colleagues and foster a collegial environment conducive to teamwork and students’ high level of learning

Essential Job Functions

Conducts a requisite number of classes/Teaches assigned subjects
Provides guidance and supervision to students
Creates and maintains

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Tenure-Track Faculty Position in Electrical and Computer Engineering – Fall 2026

The Chandra Family Department of Electrical and Computer Engineering at The University of Texas Austin has a faculty opening with a start date of Fall 2026 for a tenure-track faculty position. Candidates in all areas of electrical and computer engineering will be considered, especially as they align with the strategic focus of the department in: (i) AI/ML, including generative AI foundations and applications ; (ii) AI for systems and systems for AI; (iii) Computer architecture, with a focus on heterogeneous computing systems; (iv) Signal processing, data science, communications and information theory; and (v) Software engineering, with a focus on AI-managed middleware, software generation and applications.

We are particularly interested in candidates who will contribute to supporting our student body through their teaching, research, and service. Successful candidates are also expected to contribute to and

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Global ecosystems are undergoing unprecedented transformations driven by the rising demand for water, energy, and critical minerals. These changes are rapidly altering the Earth system, including land, air, and water, and influencing human systems, such as public health, epigenetics, migration, politics. A growing wealth of observational data from satellites, sensor networks, foundation models, gridded weather and reanalysis, socio-economic databases, and other multi-scale technologies is enabling a higher-fidelity view of the Earth system than ever before. Combing this ever-expanding ecosystem of data with advanced computational techniques, particularly the ethical and sustainable use of AI, is of high priority. The University of Utah, under the leadership of the One-Utah Responsible AI Initiative (One-U RAI,https://rai.utah.edu/), is building a new group to address a broad range of environmental challenges and opportunities created by AI by leveraging, integrating and enhancing existing strengths in earth and environmental science, biological science,

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Description

The Fariborz Maseeh Department of Civil, Architectural and Environmental Engineering (CAEE) at The University of Texas at Austin invites applications for a tenure-track assistant professor position in in riverine and coastal systems.  We seek a candidate whose research addresses critical challenges in hydrology, flood prediction, coastal and hurricane-related physical processes, and/or the impacts of extreme weather events, including protection strategies. Emphasis will be placed on research involving field studies (including remote sensing) and/or laboratory experiments. The successful candidate will show potential for interdisciplinary collaboration within the department, across campus, and with national and international partners.

We are committed to supporting the success of all members of our community: students, staff, and faculty.  A successful candidate can expect to benefit from and contribute to those efforts.

Qualifications

Candidates must have a PhD in engineering or a related area. The successful candidate will be expected

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