Front-End Interactive Platform for Deploying TelescopeML Machine Learning Package Internship

The Space Science and Astrobiology Division at Ames Research Center enables space exploration through selected development, innovative technologies, and interdisciplinary scientific discovery in Astrophysics, (exo-)Planetary systems, and Exobiology research areas. We are looking for a Data Science intern to support NASA’s Exoplanetary research team to develop ML models to extract stellar/planetary information from observational/telescope data.

Key Responsibilities:
· Deploy/implement a front-end platform to utilize trained TelescopeML models.
· Demonstrate a fundamental understanding of Machine Learning and CNN models.
· Provide scientific analytics and insights directly to the project mentor and the team.
· Collaborate closely with the project mentor and report/discuss the results.

Qualifications:
· Expertise in Streamlit, Flask, etc. and have a project ready to discuss during the interview.
· Experience in Python (e.g., Pandas, Seaborn, TensorFlow) with a strong motivation to learn more.
· Good understanding of deep neural networks (CNNs) and their applications to solve regression problems (pip install TelescopeML for more info).
· Background in computer science, science, or engineering is desirable.
· Excellent communication, collaboration, and interpersonal skills with a strong passion for working in the AI space exploration field.

Other Qualifications:
· Ability to prioritize workloads and ensure deadlines are met.
· Drive completion of action items and record and archive key findings and decisions.
· Eagerness to learn new topics and a willingness to take ML courses if needed.