Scientific Analyst

Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community.

Job Summary

IPAC, part of the Physics, Math, and Astronomy Division at Caltech (www.caltech.edu ), provides science operations, user support, data and archive services, and scientific vision to enhance discovery with observatories both in space and on the ground. We enable transformative scientific research using data from NASA Astrophysics missions.

IPAC invites applications for a full-time data science position. The selected applicant will work with members of several teams at IPAC to investigate and implement machine learning and artificial intelligence (ML/AI) techniques to improve the efficiency and effectiveness of data ingestion for the NASA/IPAC Extragalactic Archive (NED) and the NASA Exoplanet Archive .

Essential Job Duties

As a data science staff member, your job may include:

• Evaluate different machine learning methods for applicability to streamline data ingestion from the scientific literature.
• Design, develop and test a shared IPAC infrastructure and processes for applying AI/ML models to this domain, including facilitation of periodic retraining of models, which is essential to account for new data types or patterns appearing in the literature as science advances.
• Integrate the new AI assistance tools and methods into the operational processes of NED and the Exoplanet Archive, including folding in feedback from vetting by human experts to iteratively improve the AI-generated database load files.
• Write, test, and edit documentation.
• Participate in meetings (virtual and in-person).

Basic Qualifications

If you have the following in your background, then we want to hear about your interest in joining our team:

• Bachelor’s degree in computer science, astrophysics or a closely related field.
• Experience and strong interest in machine learning methods.
• Experience with programming in Python, R, or other scientific/technical computing language.
• Good written and verbal communication skills, with an emphasis on the ability to share ideas in a collaborative and diverse setting.

Preferred Qualifications

Beyond these basic qualifications, there are skills and experiences which will add to your ability to contribute to the roles and responsibilities of this position. Any of the following might give you a head start here, but even if these do not describe you or your experience, we would still like to hear from you!

• Masters or PhD in computer science, astrophysics or a closely related field.  
• Experience with implementing ML/AI techniques in a scientific application.
• Experience fine tuning modern large language models to improve accuracy in a specific domain of knowledge will be particularly advantageous.  
• Experience working with astronomical archives and familiarity with data published in the peer-reviewed astronomical literature.

Required Documents

• CV
• Cover letter
• List of three professional references.

Consideration of applications will begin August 16 and continue until the position is filled.