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locationsEducation City, Qatar
Job Title
Research Associate-Harris Rabbani
Agency
Texas A&M University
Department
Qatar Campus RVACANT
Proposed Minimum Salary
$3,200.00 monthly
Job Location
Doha, Ad Dawhah
Job Type
Staff
Job Description
Our Commitment
Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing varying opinions and perspectives strengthens our which are: Respect, Excellence, Leadership, Loyalty, Integrity, and Selfless Service.
Who we are
The Texas A&M University at Qatar campus mission is to educate exemplary engineers and develop world-class leaders through internationally recognized undergraduate and graduate degree programs. We strive to generate new knowledge and intellectual capital through innovative research and collaborative partnerships that yield sustainable impact and advance the development goals of the State of Qatar and the region through expertise and engagement that expand human capital.
What we want
The Research Associate will be developing cutting-edge computer vision algorithms to solve reservoir engineering problems and contribute to academic publications.
What you need to know
This position is NOT located in the United States. The selected candidate must be willing to relocate to Doha, Qatar. Learn more about life at Texas A&M University at Qatar by visiting this link .
Salary: $3,200 monthly; Compensation will be commensurate to selected hire’s experience.
Special Instructions: A cover letter and resume are strongly recommended. You may upload these in the CV/Resume section.
Required Education and Experience:
Appropriate bachelors degree.
Two years of related professional experience.
Required Skills:
Ability to multi-task and work cooperatively with others.
Solid understanding of computer vision principles and techniques.
Proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
Hands-on experience with deep learning architectures.
Strong programming skills in Python and proficiency with relevant libraries (e.g., OpenCV, scikit-learn).
Excellent problem-solving abilities and a passion for learning.
Required Knowledge and Experience:
Experience in Digital Rock Characterization:
Utilize AI algorithms to classify rock types and characterize their microstructures based on the extracted features.
Train machine learning models, such as regression or classification models, to predict rock properties based on the extracted features.
Identify and quantify mineral phases, fractures, pore types, and heterogeneities within the rock samples.
Modeling and Simulation:
Integrate the AI-derived rock properties into numerical simulations and computational models to predict fluid flow, mechanical behavior, and other relevant phenomena.
Use AI-based techniques to optimize model parameters and improve the accuracy of simulations.
Preferred Qualifications:
Msc
Essential Duties/Tasks:
Digital Rock Characterization - Utilize AI algorithms to classify rock types and characterize their microstructures based on the extracted features. Train machine learning models, such as regression or classification models, to predict rock properties based on the extracted features. Identify and quantify mineral phases, fractures, pore types, and heterogeneities within the rock samples.
Modeling and Simulation - Integrate the AI-derived rock properties into numerical simulations and computational models to predict fluid flow, mechanical behavior, and other relevant phenomena. Use AI-based techniques to optimize model parameters and improve the accuracy of simulations.
We are a prestigious university with strong traditions, Core Values, and a community of caring and collaboration.
, , , with Texas A&M contributing to employee health and basic life premiums.
of annual paid holidays.
Up to and at least month.
Automatic enrollment in the Teacher Retirement System of Texas.
Health and Wellness: .
Professional Development: All employees have access to free training, webinars, and limited financial support to attend conferences, workshops, and more.
and for completing a degree while a Texas A&M employee.
Instructions to Applicants:
Applications received by Texas A&M University must either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to pre-populate the online application.
All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.
Equal Opportunity/Affirmative Action/Veterans/Disability Employer.
locationsEducation City, QatarlocationsEducation City, QatarHowdy and thank you for your interest in a career with Texas A&M University. As the flagship campus of The Texas A&M University System, we are located in College Station, Texas with a student population of more than 74,000 and nearly 14,000 faculty and staff.
The Spirit of Aggieland is unmistakable. We are a unique American institution, fostering a culture of friendliness, compassion and respect for one another. Our unique history and rich traditions make Texas A&M special.
From our benefits package and professional development opportunities to our retirement programs, Texas A&M is a great place to work. Your path to a great career starts here!
Equal Opportunity/Affirmative Action/Veterans/Disability Employer.