Internship

Research Scientist

Earth and Planetary Sciences

Updated on 8/1/2026

University of Texas at Austin

University of Texas at Austin

Compensation Overview

$55k/yr

Company Does Not Provide H1B Sponsorship

Austin, TX, USA

In Person

In-person, Monday through Friday, 9 AM–5 PM; occasional interstate/intrastate travel may be required.

Category
AI & Machine Learning (1)
Required Skills
Python
PyTorch
Requirements
  • A bachelor's degree is required; relevant education and experience may be substituted as appropriate.
  • Candidates must currently be authorized to work in the United States.
  • Candidates must be able to use basic engineering and scientific equipment ordinarily used in college laboratory work.
  • Three work references with contact information are required, including at least one supervisor reference.
  • A resume or curriculum vitae and letter of interest are required.
Responsibilities
  • Conduct independent research on problems related to artificial intelligence and geoscience.
  • Develop, test, and deploy code for large-scale model training and inference.
  • Attend weekly group meetings.
  • Lead independent research efforts.
  • Collaborate with group Ph.D. students, postdoctoral researchers, and partners.
  • Complete two to three research projects, including completed manuscripts submitted to high-impact artificial intelligence venues such as ICLR, ICML, and CVPR, or top-flight journals such as Nature.
  • Maintain in-person availability for 40 hours per week, Monday through Friday, from 9 AM to 5 PM.
  • Travel occasionally interstate or intrastate for programs, events, and meetings.
Desired Qualifications
  • A postgraduate master's or Ph.D. degree from a major accredited university in a computational discipline such as Computer Science or Electrical Engineering.
  • Demonstrated capacity to conduct university-level research.
  • Publications accepted to top artificial intelligence venues such as ICML, ICLR, or NeurIPS.
  • Strong mathematics and coding abilities.
  • Proficiency in Python and modern machine learning frameworks such as PyTorch and JAX/FLAX.
  • Software engineering experience, preferably as part of a large or industrial team.
  • Familiarity with atmospheric, Earth, or geological sciences.
University of Texas at Austin

University of Texas at Austin

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