Position

This 10-week summer internship provides an opportunity to gain hands-on experience within the Software Engineering and Computational Modeling function in a collaborative, fast-paced research environment. The Software Intern will support development and application of Bayesian statistical methods, machine learning models, and computational approaches used to characterize complex single-molecule and photophysical systems. In this role, you will gain exposure to interdisciplinary scientific computing workflows that combine statistical inference, machine learning, and software development. This internship is designed to provide experience contributing to research-focused software tools, algorithm development, and computational modeling efforts that support advanced scientific discovery and platform technologies.

About You

You are passionate about computational science, statistical modeling, and scientific software development. You enjoy solving mathematically and computationally complex problems and are excited to apply programming and modeling techniques to real-world scientific challenges. You are curious, analytical, and comfortable working at the intersection of statistics, physics, and machine learning. You enjoy collaborating with scientists and engineers and are motivated to develop robust and scalable computational solutions.

What You’ll Do

• Support development and evaluation of Bayesian statistical inference methods and algorithms.
• Assist with computational investigation of variational Bayesian inference approaches, including evaluation of algorithm performance and resolution limits.
• Support development, implementation, and training of machine learning models used to characterize photophysical dynamics of single-molecule emitters.
• Assist with statistical derivations and modeling approaches supporting Bayesian inference for advanced single-molecule motion models.
• Develop and maintain research-focused software tools and computational workflows using Python.
• Analyze computational results and support interpretation of modeling and simulation outcomes.
• Collaborate with interdisciplinary teams of scientists and engineers to translate theoretical approaches into practical modeling and software solutions.
• Document methodologies, code development, and experimental findings.
• Present internship project outcomes and key learnings.

Qualifications

• Currently enrolled in an accredited university pursuing a Bachelor’s or graduate-level degree in Computer Science, Physics, Applied Mathematics, Statistics, Engineering, Computational Biology, or a related quantitative discipline.
• Entering senior year of a bachelor’s program or currently enrolled in a graduate-level degree program at the start of the internship.
• Must be enrolled in school during the internship program.
• Comfort with programming and software development in Python.
• Foundational understanding of statistics and/or Bayesian inference.
• Exposure to machine learning concepts or data science methodologies.
• Strong analytical and problem-solving skills with interest in computational modeling or statistical inference.
• Ability to clearly document and communicate technical and computational findings.
• Ability to work collaboratively in a team environment while managing independent research or software development tasks.
• Must be available to work full-time (40 hours per week) during core business hours for a minimum of 10 weeks during the summer internship program.
• Academic exposure to nonlinear dynamics, dynamical systems, transport phenomena, molecular simulation, single-molecule optics, photophysics, or related quantitative scientific disciplines is a plus.

The expected hourly pay range for this role is $36 - $48/hour. Placement within this range is determined based on education level.