Expires on: 02/10/2024
Description
Join our doctoral program in Statistics and Operations Research at UPC, under the Catedras ENIA, specifically the ENIA Chair Sustainable AI (Provisional Resolution). We invite applications for a Ph.D. position with a focus on the Development and Evaluation of Metrics for Assessing Synthetic Data Quality. The successful candidate will contribute to cutting-edge research at the intersection of AI and statistics, working on a 34-month project with a possibility of extension.
The selected candidate will work on defining metrics to evaluate the quality of synthetic data, focusing on statistical properties such as parametric distribution, comparable variance, and correlations among variables. The research will involve developing a framework to compare synthetic data with real-world data, utilizing statistical techniques like hypothesis testing, clustering, and regression analysis. The goal is to create a methodology for assessing the suitability of synthetic data for predictive models and statistical analyses, thereby enhancing decision-making processes.
Qualification
- Master’s degree in a relevant field (statistics, computer science, artificial intelligence, data science, or similar).
- Strong background in statistical inference, methods, and machine learning.
- Proficiency in programming skills in R.
- Interest in interdisciplinary research at the intersection of AI and statistics.
- Proficiency in English.
How to Apply
Interested candidates should submit the following documents to Guadalupe Gómez Melis (lupe.gomez@upc.edu) with cc to ignacio.perez.blasco@upc.edu:
- CV (free format)
- Academic transcripts
- Relevant certificates
- Research interests and motivation for applying
- Contact information for two academic references
- Other supporting materials such as reference letters