Technical projects involving ML/AI
Anastassia Fedyk, Professor
Business, Haas School
Applications for Spring 2025 are closed for this project.
This is an opportunity to work on technical projects involving ML/AI. The projects include: (i) working with a large dataset of over 400 million employment profiles (resumes) in order to understand global employment dynamics and firm performance by structuring and analyze the large textual data; (ii) building custom large language models; (iii) econometric analysis (ideal for students interested in pursuing a Ph.D. in economics) to understand the impact of AI on firms and workers. NOTE: very limited slots are available for this project, and only the most competitive and experienced students will be considered.
Role: Key tasks will include:
- Working with textual data to extract pertinent information.
- Building, training, and fine-tuning custom LLMs.
- Using a range of statistical tools (including both ML and econometrics) to perform analyses.
Students who work on this project will increase their knowledge of:
- Working efficiently with real-world large datasets in the terabytes
- Using econometric and machine learning techniques
- Understanding and conducting scientific research processes
Qualifications: Required:
- Experience with at least one of: Python, C/C++, R, Matlab, in a comprehensive way (i.e., WITHOUT excessive reliance on specific packages such as Pandas);
- Foundational computer science courses (Data Structures and Algorithms);
- Experience writing object oriented, efficient, modular code, NOT Jupyter notebooks.
Preferred:
- Foundational Statistics and/or Machine Learning courses;
- Practical experience with Econometric analysis.
Must be willing to put in 10 hours/week every week, with no exception.
Hours: 9-11 hrs
Related website: https://sites.google.com/berkeley.edu/fedyk
Digital Humanities and Data Science Social Sciences