PhD Position on Incident Response: The Semantics, Cybersecurity, and Services (SCS) group at the University of Twente, in collaboration with the Twente University Centre for Cybersecurity Research (TUCCR), is inviting applications for a PhD Position in Explainable Incident Response. The position aims to develop novel machine learning (ML) algorithms for incident response, focusing on reducing analyst workload and providing decision-making assistance through explainable ML.
- 🎓 PhD Position at TUCCR
- The University of Twente’s SCS group and TUCCR invite applications for a PhD position in Explainable Incident Response.
- Focus on addressing challenges in current Security Operations Centres (SOCs) with machine learning solutions.
- 🚀 Project Objective
- Develop AI-assisted practitioners for incident response using novel ML algorithms.
- Target reducing analyst workload and providing decision-making assistance.
- Emphasis on creating explainable ML algorithms that summarize large volumes of data for contextually meaningful patterns.
- 🌐 Scope of Research
- Exploration of multi-modal learning and generative AI for actionable explanations.
- Evaluation under closed-world and open-world settings.
- Closed-world: Establish a testbed with industry collaborators for intrusion alert datasets.
- Open-world: Deployment of algorithms in real SOC environments to measure workload reduction.
- 📚 Opportunities for PhD Student
- Embedded in the SCS group at the University of Twente.
- Potential internships and collaborations with industry partners under TUCCR.
- Stimulating and supportive research environment with opportunities for personal and professional growth.
- 📝 Application Information
- Deadline for application: 16 February.
- Required documents: Cover letter, CV, language proficiency test (IELTS, TOEFL, or Cambridge CAE-C).
- 🌐 About the Department (SCS)
- Focus on advancing innovative online services with improved quality and reduced security threats.
- Part of TUCCR, a public-private partnership dedicated to cybersecurity research with societal impact.
- 🏢 About the Organization (EEMCS)
- Faculty of Electrical Engineering, Mathematics, and Computer Science.
- Contribution to the development of ICT with a people-first approach and extensive collaboration with industry partners.
Designation: PhD Student
Research Area: Explainable Incident Response
Location: University of Twente
Eligibility/Qualification:
- MSc degree with excellent grades in computer science or similar (candidates close to finishing their MSc studies will also be considered).
- Background in systems security and/or data science/artificial intelligence.
- Proficient in Python and familiar with UNIX/Linux systems.
- Strong interest in cybersecurity.
- Industrial experience in a cybersecurity role and prior paper-writing experience is advantageous.
- Excellent analytical and communication skills.
- Proficient in English.
Job Description:
PhD Position on Explainable Incident Response – TUCCR
- Develop explainable ML algorithms for incident response to reduce analyst workload.
- Summarize large volumes of observable data using ML.
- Explore multi-modal learning and generative AI for producing actionable explanations.
- Set up a testbed for collecting intrusion alert datasets.
- Deploy algorithms in real SOC environments for evaluation.
- Contribute to the development of novel technologies with real-world applications.
How to Apply: Interested candidates should apply before 16 February via the ‘Apply now’ button on the official website. The application must include:
- A cover letter (maximum 2 pages A4) highlighting specific interests, qualifications, and motivations.
- Curriculum Vitae, including a list of courses attended, grades obtained, publications (if any), and references.
- IELTS-test, Internet TOEFL test (TOEFL-iBT), or a Cambridge CAE-C (CPE) for non-Dutch applicants.
Last Date for Apply: 16 February 2024
Disclaimer: This information is based on a reliable source. Applicants are advised to verify details and check for updates on the official University of Twente website for the most accurate and up-to-date information.
