PhD student position at the Department of Computing Science at Umeå University.
Project description
Our societies rely on computer systems, and increasingly so. Unfortunately, computer systems can be the target of malicious applications—malware. These malicious applications can be complicated pieces of software developed by well organized criminal gangs or by government agencies to attack anything from private computers and smart phones to critical national infrastructures. There has been an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include to develop novel machine learning methods to improve malware detection.
The doctoral student position is offered within a research project financed by the Wallenberg AI, Autonomous Systems and Software Program (WASP). The doctoral student will be co-supervised by Alexandre Bartel, Professor and head of the Software Engineering and Security (SES) group, and Tommy Löfstedt, Docent and Associate Professor and head of the Machine Learning group at the Department of Computing Science, Umeå University.