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Entry Level Research Assistant Machine Learning Jobs

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The research intern will be in a fast-paced start-up environment playing a crucial technical role ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The research intern will be in a fast-paced start-up environment playing a crucial technical role ...

Northeastern University

Research Assistant

Boston, MA · On-site

$48K - $66K/yr

About the Opportunity This job seeks a research assistant to work on one or more projects related ... Possible projects topics include: 1) Developing machine-learning based exoskeleton controllers to ...

NorthEastern

Research Assistant

Boston, MA

$48K - $66K/yr

About the Opportunity This job seeks a research assistant to work on one or more projects related ... Possible projects topics include: 1) Developing machine-learning based exoskeleton controllers to ...

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$224K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine ...

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Research Assistant in Materials Science and Additive Manufacturing

Research Assistant in Materials Science and Additive Manufacturing

The University of Texas Rio Grande Valley

Edinburg, TX • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

University Of Texas Rio Grande Valley rating

7.5

Company rating: 7.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

262nd of 534 rated colleges and universities

Job description

Posting Details Title Information Assistantship Title Graduate Research Assistant Job Class Code 10095 FLSA Exempt Minimum Qualifications
  • Must be admitted to a graduate degree program
  • Be in good academic standing
  • Be registered full-time for the respective semester (nine semester credit hours during the fall semester, nine semester credit hours during spring semester, three semester credit hours during the summer session(s)), or in the required number of semester credit hours to fulfill the only remaining requirements on the degree plan.
Position Information Posting Number A1346 Working Title Research Assistant in Materials Science and Additive Manufacturing Location Edinburg, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Manufacturing and Industrial Engineering Division Provost - Academic Affairs FTE .5 Scope of Job Maximum appointment is limited to twenty (20) hours per week (50% FTE) during the Fall and Spring semesters. Maximum appointment may be increased up to forty (40) hours per week (100% FTE) during the summer if funded by a grant. Dr. Ahsan's Lab in the Department of Manufacturing and Industrial Engineering at UTRGV will be immediately recruiting a motivated graduate (master's/PhD) student to start as early as Summer 2026. The selected candidate will work on a funded research project focused on developing novel alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and characterize new alloys and composites fabricated via laser powder bed fusion additive manufacturing. This work is closely woven into materials science, additive manufacturing, and machine learning realm, with applications in energy and extreme environments. The candidate will receive a monthly stipend and tuition support. Discipline Specific Required Qualifications The Research Assistant assistantship award is available to master's and doctoral students who are assigned to a specific faculty member who is conducting research or a scholarly endeavor. Duties will vary depending on the project and assigned research/scholarly functions, or other creative aspects. Preferred Qualifications
  • Bachelor's degree in Mechanical Engineering, Manufacturing Engineering, or Materials Science and Engineering
  • Master's degree in Mechanical Engineering or Materials Science and Engineering (required for Ph.D. applicants)
  • Experience with additive manufacturing, materials characterization, and/or physics-informed machine learning
  • Proficiency in Python programming is preferred
Salary Commensurate with experience. Number of Vacancies Multiple Desired Start Date 06/01/2026 Posting Detail Information EEO Statement It is the policy of The University of Texas Rio Grande Valley to promote and ensure equal employment opportunities for all individuals without regard to race, color, national origin, sex, age, religion, disability, sexual orientation, gender identity or expression, genetic information or protected veteran status. In accordance with the requirements of Title VII of the Civil Rights Act of 1964, the Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, as amended, our University is committed to comply with all government requirements and ensures non-discrimination in its education programs and activities, including employment. We encourage women, minorities and differently abled persons to apply for employment positions of interest. Open Date 01/27/2026 Special Instructions to Applicants If you are interested, please send the following ASAP to Dr. AMM Nazmul Ahsan at ammnazmul.ahsan@utrgv.edu :
  • Current CV,
  • How you meet the qualifications in 2/3 sentences or bullet points, and
  • Unofficial graduate+undergraduate transcripts.
This position is expected to be filled immediately. All applications must be submitted via the UTRGV application portal at https://careers.utrgv.edu. If you are applying for the first time, please complete all biographical information including address, email and phone. You may update this at any time by selecting to edit your profile in the application. A Criminal Background Check must be conducted for all applicants. Quick Link https://careers.utrgv.edu/postings/50078

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