PYTHON RESEARCH SOFTWARE CONSULTANT (PAID, SHORT-TERM, REMOTE)

OVERVIEW

I seek a Ph.D. or advanced graduate student in computer science or a related field with strong expertise in Python to assist in refactoring, reorganizing, and documenting two related research software codebases for publication-grade reproducibility and open-source public release.

PROJECTS

This work comprises two related components:

• PNAS Research Article Codebase
Prepare for publication the Python hierarchical Bayesian modeling (HBM) codebase underlying a manuscript soon to be submitted to PNAS on global scientific production. This codebase requires refactoring, reorganization, and documentation to meet publication-grade standards of clarity, structure, and computational reproducibility.

• Advanced Data Analytics Platform Codebase
Prepare for public release version 2.0 of an advanced data analytics platform built with Python, SQLAlchemy, and PostgreSQL as an open-source demonstration platform for research on the contemporary history of quantum information science (QIS).

This role focuses on research software engineering, code organization, documentation, and reproducibility rather than on statistical model development.

RESPONSIBILITIES

• Improve the clarity, structure, reproducibility, and maintainability of both codebases.
• Develop clear documentation, including README files, docstrings, in-code comments, and usage examples.
• Ensure reliable, reproducible execution from raw data to final analytical outputs.

SCOPE

The two codebases together include approximately 20 Jupyter notebooks, some as long as 3,000 lines. The consultant will focus on the high-priority components necessary to produce a clean, reproducible, publication-ready codebase rather than refactoring every notebook in full.

QUALIFICATIONS

• Ph.D. or advanced graduate student in computer science or a related field.
• Strong expertise in Python.
• Experience refactoring, organizing, and documenting research codebases.
• Experience preparing computational research code for peer-reviewed publication and computational reproducibility, especially code supporting a major article submission in computational social science or related fields, strongly preferred.
• Experience with hierarchical Bayesian modeling strongly preferred.
• Experience preparing codebases for open-source public release preferred.
• Experience with reproducible research practices, including environment management, workflows, and version control, preferred.
• Experience with SQLAlchemy preferred.

ADDITIONAL INFORMATION

• Duration: Flexible, approximately 80–120 hours total. All work must be completed by June 30, 2026.
• Compensation: Competitive and commensurate with qualifications and scope of work.
• Location: Remote.

HOW TO APPLY

Please send a brief statement of interest outlining your background and relevant experience, together with your CV and links to any code samples or repositories, to:

Professor Roger Hart
Department of History & Geography
Texas Southern University
[email protected]
http://rhart.org/