KU is seeking a highly motivated Research Associate to work in a project that aims to develop, deploy, and assess AI-based tools that rely on behavioral data like system-calls with other data sets like logcats, CPU usage, dumpsys and ptree to detect and classify malware\'s activities. We will investigate both raw and pictorial data representations as needed for the GAN system, considering the possibility of multi-GANs implementation. Furthermore, augmenting and data fusion should improve the GAN perception, which will be validated via error comparison between the original and the artifact samples.
As part of the project, the researcher will have access to state-of-the-art research equipment and facilities at the Center for Secure Cyber-Physical Systems and will get an opportunity to work alongside researchers and graduate students from various backgrounds as part of a wider team.
Position Requirements
Set up experimental settings for generative modeling comparisons and tuning.
Collect and prepare reliable data sets on malware behavior.
Implement specific data preparations and analysis procedures in Python
Adhere to the University\'s information security and confidentiality policies and procedures, and report breaches or other security risks accordingly
Perform any other tasks assigned by the Line Manager
Qualifications
Candidate Profile
Essential Criteria
Masters from a reputable university in Computer Science or related discipline
Experience of undertaking assigned research tasks and contributing to academic outputs
A willingness to contribute to a collaborative and supportive team culture
Excellent English language communication skills (verbal and written)
Ability to function as part of a team working on multiple tasks with competing demands and deadlines
Well-developed reasoning and problem-solving skills
Desired Criteria
Masters gained from and/or experience working in a top 200 QS or THE ranked University
At least 1 year of relevant experience as a researcher in academia or in industry
Experience contributing to high impact publications in top 10% journals in the relevant field
Should you require further assistance or if you face any issue with the online application, please feel to contact the Recruitment Team ( ).
Primary Location: Abu Dhabi UAE Job: Research Associate Schedule: Regular Shift: Standard Job Type: Full-time
Times Higher Education
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