The Plants, Soils and Climate Department is currently seeking a talented graduate student with a passion for image processing and deep learning to join our team. The project focuses on employing image and video processing and deep learning techniques to monitor water levels in irrigation canals. It necessitates extensive fieldwork for image collection and laboratory work to develop a robust model to measure water levels.
ResponsibilitiesField Surveys and Data Collection:
Install and maintain cameras and other sensors along canals and ditches in designated valleys across Utah.Conduct regular field surveys to ensure proper functioning of the equipment.Collect and log data, including water levels, and images from the installed cameras.Data Management and Preprocessing:
Clean, normalize, and preprocess collected data to ensure high quality and consistency.Maintain a well-organized database of all collected dataMachine Learning Model Development:
Develop and train machine learning models to detect and predict water levels in canals and ditches.Use regression models for continuous predictions and classification models for categorizing water levels.Implement image processing techniques using Convolutional Neural Networks (CNNs) to analyze visual data from cameras.Validation and Calibration:
Conduct field tests to validate the accuracy of model predictions against actual water level measurements.Calibrate sensors and models to improve predictive accuracy. QualificationsMinimum Qualifications:
Enrollment in a MS or PhD program.Demonstrated expertise in developing and deploying machine learning models.Proficiency in programming languages and libraries such as Python, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, and OpenCV.Proficiency in image and video processing and deep learning methodologies.Strong analytical, problem-solving, and data visualization skills.Strong communication skills for effective reporting and collaboration.Preferred Qualifications:
Experience with cloud computing platforms such as AWS, Google Cloud, or Azure for data storage and processing.Familiarity with edge computing and deploying models on devices like Raspberry Pi or Arduino.Knowledge, Skills, and Abilities:
Familiarity with IoT devices and camera-based data collection.Ability to work independently in remote field locations and as part of a multidisciplinary team.Strong aptitude for effective fieldwork.Willingness to travel frequently to various field sites in Utah. Required DocumentsAlong with the online application, please attach:
Resume to be uploaded at the beginning of your application in the Candidate Profile under “Resume/CV”
**Document size may not exceed 10 MB.**
Advertised Salary Commensurate with experience ADAEmployees work indoors and are protected from weather and/or contaminants, but not, necessarily, occasional temperature changes. The employee is regularly required to sit and often uses repetitive hand motions. The employee is frequently required to reach with hands and arms and may lift and/or move up to 10 pounds.
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About the Region
U.S. News and World Report ranked Utah first for its strong economy, fiscal stability, education, and health care. Outstanding outdoor recreational opportunities abound throughout the state, including five national parks, 43 state parks and recreation areas, and 15 alpine ski resorts. The home of USU’s main campus, Logan, is a city of 54,000-plus people in a picturesque mountain valley 80 miles north of Salt Lake City. The Logan metro area claimed the top spot in the Milken Institute’s 2022 ranking for best-performing small cities in the nation.
*updated 04/2024
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Executive Director of the Office of Equity Matthew Pinner, discrimination@usu.edu, Distance Education Rm. 401, 435-797-1266
Title IX Coordinator Cody Carmichael, titleix@usu.edu, Distance Education Rm. 404, 435-797-1266
Mailing address: 5100 Old Main Hill, Logan, UT 84322
For further information regarding non-discrimination, please visit https://equity.usu.edu/, or contact:
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*updated 09/2023
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