Looking for proactive students who want to pursue a career in research and have a strong interest in Artificial Intelligence, Cybersecurity, and Explainable AI (XAI).
The selected candidate will work closely on research-oriented projects at the intersection of Machine Learning, Deep Learning, Cybersecurity, and Explainable AI. The role will involve exploring research problems, implementing and evaluating machine learning and deep learning models, analysing experimental results and contributing to the development of interpretable and trustworthy AI solutions for cybersecurity applications.
Responsibilities
- Conduct literature reviews and analyse recent research papers in AI, cybersecurity, and Explainable AI.
- Assist in identifying and formulating research problems and hypotheses.
- Design, implement, and evaluate Machine Learning and Deep Learning models.
- Develop experiments using Python and relevant AI/ML frameworks.
- Investigate and apply Explainable AI techniques to improve the interpretability and transparency of AI models.
- Analyse datasets, model performance, and experimental results.
- Document research findings and contribute to technical reports, research papers, and presentations.
Requirements
- Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Data Science, Cybersecurity or a related field.
- Strong understanding of fundamental Machine Learning and Deep Learning concepts.
- Good understanding of model training, evaluation, and performance metrics.
- Strong Python programming skills and experience with commonly used ML/DL libraries and frameworks.
- Familiarity with libraries such as NumPy, Pandas, Scikit-learn, PyTorch, or TensorFlow.
- Genuine interest in AI research, Cybersecurity, and Explainable AI.
- Ability to read, understand and critically analyse research papers.
- Strong analytical and problem-solving skills.
- Ability to work independently, learn quickly and communicate technical ideas effectively.
