Technical projects involving ML/AI
Anastassia Fedyk, Professor
Business, Haas School
Open. Apprentices needed for the Fall semester. Enter your application online beginning August 22nd. The deadline to apply is Tuesday, September 2nd, 4pm.
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