I-22014-POSTDOCTORAL POSITION IN PRIVACY-PRESERVING FEDERATED MACHINE LEARNING FOR ATTACK DETECTION
Are you passionate about research? So are we! Come and join us
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.
You ‘d like to contribute as a researcher? Join our IT for Innovation Services department
The IT for Innovative Services (ITIS) department, with its 100 researchers and engineers, focuses on the digital transformation of operations in organizations with traditional environments and digital ecosystems, with the aim of improving their performance and innovation capacity. The common thread throughout ITIS is to develop the most efficient use of big data to ensure the most appropriate decision-making processes.
The department relies on the Data Analytics Platform: a hybrid infrastructure covering the entire range of data analytics activities. The platform is based on three pillars: a high-performance computing (HPC) infrastructure, a cognitive analytics pillar and an interactive visualization wall (Viswall).
How will you contribute?
We are looking for a highly motivated candidate with proven skills in security and privacy-preserving machine learning to work on a research project funded by FNR (Luxembourg) and ANR (France). The ongoing deployment of new communication technologies related to 5G opens new doors to the implementation of cooperative, connected and automated mobility applications. However, more time is needed before all these technologies are fully deployed and with a satisfactory level of security and privacy. This is even more critical in cross-border areas such as between Luxembourg and France, where a large number of attacks (e.g., related to roaming) may arise. In this context, the main mission of the candidate will be to design and evaluate machine learning based attack detection solutions based on network traffic data generated by a vehicular network (V2X).
The specific missions of the candidate will include, but are not limited to:
- Design machine learning based attack detection solutions, where attacks have been specified in project deliverables.
- Implement the designed solutions in a federated machine learning framework, so that machine learning models can be trained based on data from different sources in the cross-border setting.
- Evaluate the solutions based on real-world and simulated datasets.
- Integrate the solutions on a Blockchain infrastructure provided by other partners in the consortium.
Is Your profile described below? Are you our future colleague? Apply now!
- PhD in Computer Science with an information security background
- Background in privacy protection and cryptographic primitives, and experience in implementing and evaluating solutions based on those technologies
- Background in machine learning, particularly federated machine learning, and experience in machine learning based fraud detection implementation and evaluation.
- Good level both written and spoken English.
- Knowledge in communication networks. Experience in VANETs.
- Previous experience in network and road simulation.
- French is appreciated
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 such as our Viswall, high-scale incubators and top of the range 3D/4D printings that are part of our toolkit for excelling in all we do;
Multicultural and international work environment with more than 45 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, flexible working hours, 13-month salary, statutory health insurance and access to lunch vouchers;
Personalized learning programme to foster our staff’s soft and technical skills;
An environment encouraging curiosity, innovation and entrepreneurship in all areas.
Your application must include:
- A motivation letter oriented towards the position and detailing your experience;
- A scientific CV with contact details;
- List of publications (and patents, if applicable);
- Contact details of 2 references.
Application procedure and conditions:
- LIST is an equal opportunity employer and is committed to hiring and retaining diverse personnel. We value all applicants and will consider all competent candidates for employment without regard to national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age or disability;
- Applications will be reviewed on an ongoing basis until the position is filled;
- An assessment committee will review the applications and select candidates based on guidelines that aim to ensure equal opportunities;
- The main criteria for selection will be the correspondence of the existing skills and expertise of the applicant with the requirements mentioned above.
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