Lecturer - Digital Forensic

Role Overview

This position is a full-time academic role within the Department of Computing and Information Technology, where the successful candidate will teach, supervise, and conduct research in data science, cyber security, digital forensics, and related fields. Beyond classroom instruction, the role contributes to the university’s strategic research agenda, supports postgraduate student mentorship, and helps shape curriculum that meets both industry and national security needs.

Key Responsibilities

• Deliver lectures and practical sessions at undergraduate and postgraduate levels in data science, cyber security, digital forensics, and computer security.
• Supervise student research projects, theses, and dissertations, ensuring academic rigor and alignment with current industry practice.
• Develop and continuously update course materials, assessments, and teaching methodologies to reflect emerging threats and analytical techniques.
• Conduct high-quality research that leads to publication in refereed journals and contributes to the university’s research output.
• Secure research funding and engage in collaborative projects with governmental, academic, or industry partners in areas of cyber security and data analytics.
• Provide academic advising and mentorship to students, including guidance on professional certification and career pathways.
• Participate in departmental committees, curriculum reviews, and accreditation processes as required by the university.
• Contribute to community outreach and capacity-building initiatives related to digital security and data science.

Requirements & Qualifications

• A PhD in Data Science, Computer Security and Forensics, Digital Forensics, Cyber Security, or a closely related discipline from an accredited and recognized university.
• A minimum of 24 publication points, with at least 16 points derived from articles published in refereed journal papers.
• Registration with the relevant professional body in computing, cyber security, or data science, where applicable.
• Demonstrated experience in academic research, evidenced by a strong publication record and successful supervision of students at the postgraduate level.
• Hands-on proficiency in tools, programming languages, and frameworks commonly used in data science and digital forensics (e.g., Python, R, SQL, Wireshark, EnCase, or similar).
• Excellent communication and presentation skills, with the ability to engage diverse student groups and professional audiences.
• A strong record of ethical practice, academic integrity, and adherence to institutional policies.