Doctoral student in Computer Science with a focus on AI Runtime Security Assurance
Ref no: ORU 2.1.1-01649/2026
Örebro University and the School of Science and Technology are looking for a doctoral student (PhD student) for the doctoral programme in Computer Science, concluding with a doctoral degree.
Start date: 1st of May 2026
Project description
The multi-disciplinary centre for cyber resilient AI, RESIST, is a national effort funded by the Swedish Strategic Research Foundation (SSF) to bring together leading researchers in AI and cybersecurity to develop novel solutions to cyber resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by pioneering cyber resilience across the AI lifecycle. The research program focuses on four key themes: Trustworthy and Verifiable AI, Runtime Security Assurance, Robust and Secure AI-Supported Development, and Resilient Distributed and Agentic AI. RESIST will drive world-class research in the intersection between AI and cybersecurity through a strong, stimulating and well connected international research environment. Research outcomes will be validated in realworld scenarios with industry and public-sector partners. RESIST will also serve as a national hub for cyber resilient AI, promoting education, knowledge sharing, and policy development.
This PhD position is associated with the research theme Runtime Security Assurance.
Once trained, AI models can be deployed in a variety of environments, ranging from public repositories such as Hugging Face, to proprietary cloud-based platforms, following the Model-as-a-Service (MaaS) paradigm. These models, whether convolutional neural networks (CNNs), recurrent neural networks, large language models (LLMs), or large reasoning models (LRMs), are designed to respond at inference phase to user-provided inputs with meaningful outputs. However, this significantly broadens the attack surface, increasing the risk of inference-time threats that exploit model interactions with external queries. These threats can undermine robustness, compromise privacy, or circumvent alignment safeguards.
In this project, the PhD student will investigate the protection of AI models at runtime, addressing multiple stages of the inference pipeline. The research will focus on developing techniques to ensure both output reliability under adversarial input attacks and dependable model behaviour in the presence of malicious or policy-subverting prompts. In particular, the project will study mechanisms to defend large language models (LLMs) and large reasoning models (LRMs) against jailbreak attacks and other forms of behavioural manipulation. In addition, the project will develop methods to mitigate inference-time privacy leakage and unauthorized model replication. The overall objective of the thesis is to integrate these techniques into a unified framework for runtime security assurance of AI models. The research is tightly integrated with other research themes within the centre.
Supervision: The doctoral student will be supervised by Professor Mauro Conti (primary) and Dr. Alberto Giaretta (secondary).
The programme and the doctoral studentship
The doctoral programme consists of courses and an independent research project that you will present in a doctoral thesis. The programme concludes with a doctoral degree and comprises 240 credits, which corresponds to four years of full-time study.
Our ambition is for your doctoral studies to be stimulating and purposeful throughout the programme until you have obtained your doctoral degree. A thorough introduction will therefore get you off to a good start and provide a solid foundation on which you can build your studies. As a doctoral student at Örebro University, you will be offered a specially tailored seminar series, covering matters ranging from doctoral programme rules and careers to support during the study period and networking.
The place on the programme is linked to a full-time doctoral studentship for the duration of the study programme, which corresponds to four years of full-time study. More information on doctoral studentships, part-time studies and part-time doctoral studentships can be found in the Regulations Handbook. The initial salary for a doctoral studentship is SEK 32,300 a month.
Entry requirements and selection
For admission to doctoral studies, applicants are required to meet both general entry requirements and specific entry requirements. In addition, applicants must be considered in other respects to have the ability required to benefit from the programme. For a full account of the entry requirements, refer to the admissions regulations as well as to annex 2 to the general syllabus for Computer Science.
Applicants meet the general entry requirements if they
- have been awarded a second-cycle qualification,
- have satisfied the requirements for courses comprising at least 240 credits, of which at least 60 credits were awarded in the second-cycle, or
- have acquired substantially equivalent knowledge in some other way in Sweden or abroad.
Applicants meet the specific entry requirements for doctoral studies in Computer Science if they have been awarded a Degree of Master of Science in Engineering or a one-year Master’s degree from a programme within the subject field or related subjects, or if he or she has received a passing grade of at least 120 credits, including an independent project of at least 15 credits, in a main field of study of relevance to the computer science field. At least 30 credits of the 120 credits must have been awarded in the second cycle. A person who has acquired substantially corresponding knowledge, in Sweden or abroad, also meets the specific entry requirements.
Information
For more information about the programme and the doctoral studentship, please contact Dr. Alberto Giaretta, email: alberto.giaretta@oru.se and/or Prof. Mauro Conti, email: mauro.conti@oru.se. For administration issues, contact Head of Unit Martin Magnusson, email: martin.magnusson@oru.se.
At Örebro University, we expect each member of staff to be open to development and change; take responsibility for their work and performance; demonstrate a keen interest in collaboration and contribute to development; as well as to show respect for others by adopting a constructive and professional approach.
Örebro University actively pursues equal opportunities and gender equality as well as a work environment characterised by openness, trust and respect. We value the qualities that diversity adds to our operations.
Application to the programme and for the doctoral studentship
The application is made online. Click the button “Apply” to begin the application procedure.
For the application to be complete, the following electronic documents must be included:
- CV
- Proof that you meet the general and specific entry requirements (copies of the original certificate and official transcript for bachelor's and master's degrees)
- Independent project (degree project)
- Other relevant documents, course and degree certificates verifying eligibility
- Description of research interests - explaining why you are interested in this project and why you would be a good candidate for the role (1 page)
As a main rule, application documents and attachments are to be written in Swedish, Danish, Norwegian, or English. Certificates and documents in other languages verifying your qualifications and experience must be translated by an authorised translator to Swedish or English. A list of authorised translators can be obtained from Kammarkollegiet (the Legal, Financial and Administrative Services Agency), www.kammarkollegiet.se/engelska/start.
When you apply for admission, you automatically also apply for a doctoral studentship.
More information for applicants will be found on our career site: https://www.oru.se/english/career/available-positions/applicants-and-external-experts/
The application deadline is 1st of April, 2026. We look forward to receiving your application!
As we have already made our choices in terms of external collaboration partners and marketing efforts for this recruitment process, we decline any contact with recruitment agencies and advertisers.
As directed by the National Archives of Sweden (Riksarkivet), we are required to deposit one file copy of the application documents, excluding publications, for a period of two years after the appointment decision has gained legal force.
