Research Associate-Harris Rabbani

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 core values 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 https://www.qatar.tamu.edu/i-am/faculty-and-staff .

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.

Why Texas A&M University?

We are a prestigious university with strong traditions, Core Values, and a community of caring and collaboration. 

• Health , dental , vision , life and long-term disability insurance with Texas A&M contributing to employee health and basic life premiums.

• 12-15 days of annual paid holidays. 

• Up to eight hours of paid sick leave  and at least eight hours of paid vacation each month.

• Automatic enrollment in the Teacher Retirement System of Texas. 

• Health and Wellness: Free exercise programs and release time .

• Professional Development: All employees have access to free LinkedIn Learning  training, webinars, and limited financial support to attend conferences, workshops, and more.

• Employee Tuition Assistance and Educational Release time   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.