Graduate School Positions - Unique Opportunities for PhD Students in Cybersecurity

Cybercampus Sweden is proud to announce the upcoming launch of its PhD school - an eagerly awaited initiative with a unique structure, as well as the first national PhD school on cybersecurity.

The PhD school will in its first round include 15 PhD positions employed at 15 different academic partners. Each PhD project will be co-supervised by experts from at least two participating Cybercampus partners. This collaborative model allows us to bring together knowledge from different fields and enables research efforts that go beyond what individual institutions can achieve on their own. The launch of the PhD school marks a significant step forward in our commitment to building a more cyber-secure Sweden.

Being part of the PhD school will enable you to do research at excellent Swedish Universities and research centers in cooperation with Cybercampus Sweden. PhD students will benefit from extraordinary networking opportunities, an outstanding interdisciplinary PhD training program in cybersecurity and cybersecurity research infrastructures and support that will be available at the partner organizations and the Cybercampus Sweden facilities. PhD students will be employed for 4-5 years and will in addition to an attractive salary also receive travel and mobility grants for visiting other Cybercampus partners.

Currently open positions

Ph.D. student position in computer science at Blekinge Institute of Technology

The PhD student will be part of the newly established Cybercampus Graduate School (About Cybercampus Graduate School) and will work on a joint PhD project in close cooperation with researchers from Örebro University, who will serve as co-supervisors with their expertise in usable security and AI. The PhD student will work on a PhD project titled: “Distributed Intelligence for Cybersecurity in Industry 5.0 and Critical Infrastructures: From Data Fusion to Intelligence Fusion”. The aim of the project is to develop a framework based on collaborative AI concept, e.g., Agentic AI or other collaborative Large Language Models (LLMs), that synthesizes actionable intelligence from distributed, heterogeneous data sources (from both IT and OT environments), enabling more accurate, timely, and resilient cyber threat detection and response for Industry 5.0 and critical infrastructure environments.

Read the Swedish version of the ad.

Doctoral student in Trustworthy and Resilient IoT Swarm Security at Chalmers University of Technology

This doctoral student position is part of a national newly started Doctoral student school in cybersecurity, where we in particular focus on developing security mechanisms for large-scale Internet of Things (IoT) systems operating under strict resource constraints.

IoT devices are increasingly deployed in swarms for mission-critical applications such as disaster response, autonomous drone systems, intelligent transportation, and industrial automation. These systems often rely on low-power operation, function with limited supervision, and are deployed in dynamic and challenging environments. Ensuring the integrity and trustworthiness of such deployments remains a fundamental challenge, particularly when traditional centralized security mechanisms are impractical.

Your work will focus on the development of lightweight and decentralized security mechanisms for large-scale IoT swarms, enabling reliable assessment of device trustworthiness without reliance on centralized control. The research is expected to explore novel approaches to distributed trust and verification, combining system-level security mechanisms with emerging technologies to support scalable, robust, and long-term secure operation of resource-constrained IoT platforms.

Doctoral student in Computer Science at Karlstad University

The Faculty of Health, Science, and Technology is advertising a position within its doctoral program leading to a PhD in Computer Science. This PhD position is part of the Privacy and Security research group (PriSec) at the Department of Mathematics and Computer Science at Karlstad University. Research within PriSec is specialized in privacy-enhancing technologies (PETs) and privacy engineering, network security, and usable security and privacy.

The PhD student will be part of the newly started Cybercampus Graduate School and will work on a joint PhD project in close cooperation with researchers from Jönköping University, who will particularly contribute as co-supervisors with their complementary interdisciplinary perspectives and expertise in usable security and privacy research, and in Human Computer Interaction (HCI) and AI / Robotics.

PhD Position in Automated Security Testing for Critical Infrastructure, Linköping University

Cyber threats to critical infrastructure—such as energy grids and digitized transport—are a growing societal concern. The AutoSecTest project aims to revolutionize how we defend these systems by developing automated methods for security testing, evaluation, and mitigation.

As a PhD student, you will contribute to a research agenda that bridges the gap between human expertise and automated tools. You will explore the integration of Generative AI/Machine Learning with formal methods like symbolic execution and model checking to detect and patch vulnerabilities in complex Operational Technology (OT) environments.

Doctoral student in Electrical Engineering at Lund University, LTH

The Division of Secured and Networked Systems within the Department of Electrical and Information Technology at Lund University, the Faculty of Engineering, LTH, works broadly with research within Cryptography, Computer Security, Wireless and Fixed Networks. The security group has around 20 members. The main research directions are Cryptography, Privacy and System Security for Connected Systems.

We now offer a doctoral student position in the area of Cybersecurity and Software Engineering.

The position is in collaboration with the Department of Computer Science, which covers a broad range of topics, as Theoretical Computer Science, Parallel Systems, Robotics, Software Engineering and Technology. The software engineering group has around 15 members and work with both software and AI engineering topics, with a strong empirical focus and industry collaboration.

PhD in Computer Science with a specialisation in Game Theory and Cybersecurity at SDU

The Swedish Defence University is an internationally leading higher education institution in the fields of defence, crisis management, and security. We offer a unique academic environment where civilian and military perspectives meet. We educate civilian and military leaders, experts, and researchers who will analyse and manage today’s and tomorrow’s crisis situations and security challenges. The Swedish Defence University trains Sweden’s officers and leads the academic development of the officer profession. We conduct research in law with a focus on operational law and international humanitarian law, defence systems, war studies, leadership and command, military history, and political science.

The PhD project aims to study a selection of cyber-related conflict applications in which systematic unpredictability is the key to success. Together, these studies span the breadth of cyber applications, contributing to a toolbox inspired by algorithmic game theory that will provide Sweden with an asymmetric advantage in terms of being able to address widely differing types of cyber threats—differing, for example, in symmetry/asymmetry, incentive structures, and more. Such differences may, for instance, mean that what is game-theoretically optimal in itself becomes suboptimal when taking into account a particular adversary’s limited depth of reasoning.

(Note that the language in the linked site is in Swedish for the time being.)

PhD Position in Information Technology with a focus on cyber and information security, Skövde University

PhD student in Computing Science with focus on Software Lifecycle Security at Umeå University

Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.

Our societies rely on computer systems and on software stacks. Unfortunately, software systems contain bugs and vulnerabilities which can be exploited by malicious actors. This project will be conducted in the Software Engineering and Security (SES) group. The student will conduct an in-depth investigation of the software patching process and develop new methodologies to improve it. The project aims at reducing the negative impact on confidentiality, integrity and availability of software systems. Additional context specific constraints such as sensitive devices running in a medical environment could be considered.

PhD Student in Cybersecurity and Artificial Intelligence at Uppsala University

The position will be in the Emerging Communication Systems (ECoS) group that investigates the intersection of wireless communications, machine learning, low-power design, and security. Our research explores the synergies between these domains to enable future distributed communication systems that are energy-efficient, robust, and secure. As a PhD student, you will become part of a leading and growing research environment. We publish in leading international journals and conferences and collaborate internationally.

The project investigates lightweight, robust, and explainable AI-based approaches for intrusion detection in resource-constrained Internet of Things (IoT) environments. Since many IoT devices operate under strict limitations in computation, memory, and energy, the research will explore resource-efficient machine learning techniques that enable low-latency detection of malicious activity directly on devices or at the network edge. The work will address challenges such as evolving attack strategies and changing data distributions, while also considering the need for transparent and trustworthy detection mechanisms. Positioned at the intersection of cybersecurity, machine learning, and embedded systems, the project aims to advance practical methods and software tools that improve the security of IoT systems deployed in constrained and dynamic environments.