What are the responsibilities and job description for the Internship - Applying Machine Learning to Characterizing Earth-like Biosignatures and Habitability position at CRESST II?
This project tackles trying to solve the problem of using artificial intelligence/machine learning (AI/ML) to predict habitability and/or detect biosignatures from planetary spectra. These spectra will be simulated as close as possible to the data we expect to receive from the new NASA flagship mission Habitable Worlds Observatory (HWO).
The project has several parts:
• Scientific question formulation (e.g., what exactly do we consider habitability, or biosignatures? How do we translate this objective into actual insight we can gather from the data? What type of data do we need to achieve this?)
• Dataset creation (using simulators and potentially using similar real-world data)
• Data preprocessing and manipulation
• Model architecture development
• Training, testing and evaluating model performance/accuracy
• Iterative loops of development on data and AI/ML models to increase performance, accuracy, efficiency
The intern will mainly focus on the science tasks related to this work. These could include assisting in the dataset creation, literature review of the current state of the field, guiding the scientific direction and objective of the project, etc. A background knowledge of atmospheric modeling and familiarity with programming is preferred, but we encourage enthusiastic students to apply regardless of their experience level. The intern will be tasked with a small but impactful subset of what is listed, based on which stage the project is in at time of onboarding. The intern will have the opportunity to contribute to various parts of the aforementioned iterative loops of project development based on the intern’s interests and skillset.
Preferred Skills:
- Atmospheric Science Knowledge
- Familiarity with programming and data analysis
- Skills in managing large datasets
- Experience working in a collaborative research environment/willingness to engage in interdisciplinary teams
Stipend Amount: Undergraduates receive a stipend up to $8,200. Graduates receive a stipend up to $9,900.
Dates of Internship: This summer internship will begin on Monday, June 2, 2025 and end on Friday, August 8, 2025. Deviations from this specific period are possible with the agreement of the designated mentor.
