INT-26045- INTERNSHIP POSITION FOR PRIVACY-PRESERVING FEDERATED LEARNING

The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

Do you want to know more about LIST? Check our website: https://www.list.lu/

Your LIST benefits

• An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
• Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
• Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
• An environment encouraging curiosity, innovation and entrepreneurship in all areas
• Multicultural and international work environment with more than 50 nationalities represented in our workforce
• Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
• Gender-friendly environment with multiple actions to attract, develop and retain women in science
• 32 days’ paid annual leave, 11 public holidays

Internship contract | Belval | 3 Months

Are you passionate about research? So are we! Come and join us

How will you contribute?

Describe the main responsibilities of the position.

You will be mainly in charge of:

• Investigate and benchmark Federated Learning Schemes
• Develop privacy means for Federated Learning Schemes
• Implement robustness and trustworthiness solutions for Federated Learning

Is your profile described below? Are you our future trainee? Apply now!

Education

• Hold a BSc. / MSc. degree(s) in Computer Science or related discipline focused on Cybersecurity concepts
• Have good programming skills (particularly experience on Python, C++)
• Experience and knowledge on Federated Learning concepts including attacks targeting FL schemes is a plus (i.e. data poisoning, membership inference attacks, etc.)
• Experience on data preprocessing (particularly healthcare data) is a plus

Language skills

• Fluency in English, both oral and written. Other relevant languages are an asset.