Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
. For general application assistance or if you have questions about a job posting, please contact Human Resources at 479.575.5351. Department: Facility Operations & Maintenance Support Department's Website: https
-
Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
-
efficiency and reliability. Strong background in data analytics, leveraging insights to drive operational improvements and predictive maintenance. Experience in control strategies and automation, ensuring
-
variety of mechanical components and systems, fan systems, fluid power systems, and air supply systems on campus with a strong emphasis on applying preventive and predictive maintenance practices. Nature
-
maintenance of datasets, models, and data integrity checks. Support institutional data governance and ensure data quality. · Research, Analytics, and Reporting- Lead the design and execution of complex data
-
of field measurements with 3D Doppler-LIDAR and ultrasonic anemometers, high-fidelity CFD simulations, and controlled experiments. AI-supported methods for spatiotemporal prediction of microclimatic
-
Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
evaluation, and predictive maintenance. The work also address user comfort and indoor environmental quality (IEQ) as key dimensions of infrastructure performance. This research forms part of a broader effort
-
experimentally verify the predicted hit and lead compounds. By working together in a collaborative and intellectually stimulating environment, you will have the opportunity to contribute to a large number of
-
, Maintenance (Corrective, Preventive, Predictive, Reactive), coordinating with engineers, campus construction services department, and contractors on construction projects that impact the utility distribution
-
, optimisation, and predictive maintenance Good understanding of engineering system deployment, including industrial design constraints, compliance requirements, and operational safety considerations Proven track