Postdoc position in Machine Learning and Cybersecurity
The Université de Sherbrooke’s Cybersecurity Lab GRIC is happy to announce a postdoc position in machine learning and cybersecurity. The Cybersecurity Lab is a leader in research and innovation in cybersecurity. It has access to advanced infrastructure in high-performance computing and 5G allowing to explore, develop and test innovative cybersecurity solutions. The Lab collaborates with various public, financial and industrial organizations and respond to their needs on the current and future cybersecurity issues, including but not limited:
- Cyberattacks in industrial control systems and information technology systems.
- Internal threat management and associated financial crime.
- Digital identity management.
- Evolution of cryptography in a quantum era.
- Advanced intrusion detection techniques.
The postdoc candidate is expected to conduct a scientific research in the field of machine learning and intruder detection in industrial control networks. He is expected to:
- Possess a knowledge of the machine learning field, including deep learning, as demonstrated by a track record of publications in the field at top conferences and journals.
- Be familiar with existing machine learning tools as well as have a practical experience with developing machine learning applications.
- Be familiar with the basics of networking protocols.
Additional knowledge on the fields of network intruder detection and anomaly detection is an advantage.
The scholarship is 57 500 $ CAD per year, – exempt of income taxes for candidate who qualify, and most do. If the income tax exemption is approved, that would be equivalent to a salary of 85 000 $ 1CAD for someone having to pay income taxes.
The position is available immediately, for one year, renewable. Candidates will be reviewed as they arrive.
- TO APPLY, Please send the following documents, in PDF format, to email@example.com.
|• Academic CV|
• Motivation letter. Please highlight your three most impactful publications amongst other things in the letter
• PhD thesis
|• Name of 3 persons who can provide references. |
• If available, github or other link to evidence of concrete applications of machine learning