Ph.D. student position in Privacy-preserving decentralized learning

Location: Sweden
Application Deadline: November 30, 2024
Published: 12 hours ago

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About the project
Traditional machine learning requires centralizing data, posing significant privacy and security concerns. Federated learning offers a transformative solution by enabling decentralized model training without the need to share raw data, thus preserving user privacy. However, federated learning is not without vulnerabilities. Shared models are susceptible to information extraction attacks that jeopardize user privacy, and poisoning attacks by malicious clients can steer the model toward undesirable outcomes.

This project seeks to provide a fundamental understanding of the privacy and security vulnerabilities inherent in federated learning, with the ultimate aim of making it a viable option for highly sensitive sectors such as healthcare and finance. Join us in pioneering innovative solutions to these challenges and help shape the future of privacy-preserving machine learning!

Why join us?
As a Ph.D. student, you will work under the supervision of Prof. Alexandre Graell i Amat and become an integral member of a dynamic, ambitious research group specializing in privacy-preserving machine learning. Our team currently includes two Ph.D. students and one postdoc, with a second postdoc recruitment underway. You will benefit from close collaboration with AI Sweden, the Swedish national center for applied artificial intelligence, and receive co-supervision from Dr. Johan Östman at AI Sweden. Additionally, you will collaborate with leading institutions, including the Technical University of Munich (Germany) and Aalto University (Finland).

At Chalmers, you will engage in interdisciplinary research at an internationally renowned institution, exploring fields such as machine learning, information theory, and signal processing.

Read more about doctoral studies at Chalmers here.

Applicant profile
We seek candidates with:

  • An M.Sc. degree corresponding to at least 240 higher education credits in Computer Science, Mathematics, Electrical Engineering, or a related field.
  • A strong foundation in mathematics and machine learning.
  • Excellent verbal and written communication skills in English.

Position details

  • Duration: Approximately 4.5 years, including 6 months of teaching responsibilities.
  • Salary: Starting gross salary of 34,550 SEK/month, increasing to 39,550 SEK/month after 2–2.5 years.
  • Benefits: Comprehensive healthcare, social benefits, pension, and student housing options.

About the department
At the Department of Electrical Engineering, we conduct internationally renowned research in artificial intelligence, information and communication theory, biomedical engineering, signal processing, and image analysis. We offer a dynamic and international research environment with about 300 employees from more than 20 countries, and with extensive national and international research collaborations with academia, industry and society. The department provides more than 70 advanced courses for Ph.D. students.

Why Chalmers?
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

How to apply
The application should be written in English. Attach the following PDF files (maximum size 40 MB each):

  • CV: Include details of previous employment and positions of trust, plus two references.
  • Personal letter: 1-3 pages introducing yourself, detailing relevant experience, and outlining your goals and research interests.
  • Other documents: Copies of your thesis, attested copies of education transcripts, and certificates, such as TOEFL results, if applicable.

Use the application button at the bottom of this page.

Please note: Incomplete applications or those sent via email will not be considered.

Application deadline: November 30, 2024

Contact information
For inquiries, please contact:
Prof. Alexandre Graell i Amat
Email: alexandre.graell@chalmers.se

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***

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