Two PhD positions at the atlanTTic Research Center
|Published||October 26, 2022|
2 PhD positions are available at the AtlanTTic Research Center (https://atlanttic.uvigo.es/en/) from the Universidade de Vigo. The positions are available to start at the end of 2022, covering a duration of 3-4 years, and including travel budget for attendance to conference and summer schools.
The workplace is in the city of Vigo, being ranked by OCU as the Spanish city with the highest life quality (https://www.idealista.com/en/news/lifestyle-in-spain/2021/06/02/13426-qu...).
Both positions are funded by TRUMPET (https://cordis.europa.eu/project/id/101070038), which is an European project whose aim is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a scalable Federated AI service platform for the analysis of cross-border European datasets. The privacy guarantees of the platform will be validated for the scenario of cancer data coming from different European hospitals.
PhD candidates will contribute to two different central aspects: (1) research and implementation of secure methods for machine learning, and (2) measure the existing privacy leakage in federated learning scenarios.
- Research and develop novel methods to enhance the privacy of federated learning.
- Implement and evaluate their impact on data privacy.
- Run of experiments and simulation of realistic conditions to test performance.
- Management of scientific reports and publication of the obtained results in scientific journals and/or conference proceedings.
- Master’s degree or equivalent in Electrical/Telecommunications Engineering, Computer Science, Mathematics or similar, and strong background in either cryptography or machine learning.
- Good communication/writing skills in English.
- Good programming skills and flexibility to work with different secure computation and machine learning libraries.
- Experience in domains such as cryptography, secure multi-party computation, probability theory, information theory, and machine learning will be positively evaluated.