Neural Network Researcher - Cyber Security Domain (5-10 yrs)

Overview :

Unitres is seeking skilled professionals to join our cutting-edge European project focused on developing a simplified neural network that mimics brain activity, with a particular emphasis on cybersecurity applications. The project aims to explore the capabilities of spiking neural networks, using synthetic data for foundational experimentation and laying the groundwork for applying these techniques to real-world scenarios.

Key Responsibilities :

- Neural Network Design : Develop a two-layer infrastructure utilizing spiking neural networks to emulate brain-like activity.

- Synthetic Data Experimentation : Conduct foundational experiments using synthetic data to simulate cybersecurity scenarios.

- Research & Development : Work with the team to overcome technical challenges related to implementing spiking neural networks without requiring specialized hardware.

- Refinement of Techniques : Collaborate to refine the neural network technique, preparing for its application to specific cybersecurity domains.

Mandatory Qualifications :

- Educational Background : PhD or Master's in Artificial Intelligence, Machine Learning, Cybersecurity, or a related field.

- Cybersecurity Expertise : Proven experience in applying AI/ML techniques to cybersecurity challenges, such as threat detection, anomaly detection, and network defense.

- Experience in Neural Networks : Strong background in neural networks, particularly spiking neural networks, and their applications.

- Technical Skills : Proficiency in Python, TensorFlow, PyTorch, or other deep learning frameworks. Familiarity with synthetic data generation and its use in cybersecurity.

- AI/ML in Cybersecurity : At least 2 years of hands-on experience in applying AI/ML models specifically within cybersecurity, such as for identifying cyber threats, securing data, or enhancing automated defense systems.

- Problem Solving : Ability to identify and resolve challenges in the implementation of neural networks without specialized hardware.

- Research-Oriented : Experience in research projects with a focus on theoretical development and practical experimentation.