Research Aide - PHY - Shuford, Annie - 8.19.26

Argonne National Laboratory•Lemont, IL

3d•Onsite

About The Position

The student will develop the mathematical and computational framework for an adaptive spectroscopy analysis and machine-learning demonstrator within the broader GENESIS project. The work will focus on implementing adaptive fitting and data-selection methods and testing them on real experimental spectroscopy data to demonstrate improvements in analysis efficiency, precision, and use of experimental data.

Requirements

Background in mathematics, physics, computer science, or a related quantitative field.
Experience with Python, LLMs and scientific computing.
Familiarity with numerical methods, statistical data analysis, and parameter estimation/fitting.
Basic knowledge of machine-learning methods.
Ability to develop, test, and document scientific software.
Interest in applying mathematical and machine-learning methods to experimental physics data.
Currently enrolled in undergraduate or graduate studies at an accredited institution, or graduated within the past 3 months, or actively enrolled in a graduate program at an accredited institution.
Must be 18 years or older at the time the appointment begins.
Must possess a cumulative GPA of 3.0 on a 4.0 scale.
Must complete a satisfactory background check.

Responsibilities

Implement adaptive fitting and data-selection methods.
Test adaptive fitting and data-selection methods on real experimental spectroscopy data.
Demonstrate improvements in analysis efficiency, precision, and use of experimental data.