Doctoral student in Computer Science with a focus on AI and cybersecurity

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Description

The Faculty of Health, Science and Technology invites applications for a doctoral studentship in Computer Science at the Department of Mathematics and Computer Science.

The position is part of SPLAIM (Security and Privacy of Locally-Run AI Models), a research project funded by the Swedish Knowledge Foundation. SPLAIM investigates how local large language models (LLMs) can be securely, privately, and efficiently deployed in real-world organisational and business environments.

The doctoral research will focus on the technical development of efficient, secure and privacy-preserving local AI systems. This includes the design, implementation and evaluation of local LLM-based solutions and their supporting infrastructure. The work will address research questions on security and privacy risks in locally deployed AI, privacy-preserving training and inference, and performance efficiency under resource constraints.

The doctoral student will contribute to the development and assessment of methods such as parameter efficient fine-tuning, retrieval-augmented generation (RAG), hardware-aware optimization, and benchmarking of local AI models. The work will be grounded in real-world use cases identified together with the project’s industrial partners and will contribute to prototype development and evaluation in realistic settings.

The doctoral student will be involved in several stages of the research process, from requirement analysis and technical design to prototyping, experimentation, and evaluation. The position includes close collaboration with SPLAIM’s industrial partners and will be carried out within the Privacy and Security (PriSec) research group at the Department of Mathematics and Computer Science.

Duties

As a doctoral student, you will primarily dedicate time to your own studies. The doctoral programme comprises 240 credits for a Degree of Doctor and 120 credits for a Degree of Licentiate. The doctoral appointment is a paid position that offers a combination of studies and work, and a great opportunity for a potential career in academia. Doctoral students are expected to work independently and be prepared to contribute to the activities and development of the discipline and the department. You are given the opportunity to deepen your interests in collaboration with others. Teaching and administrative duties may also be included upon agreement, but will not constitute more than 20% of full-time. Work as a doctoral student allows for great freedom and flexibility in terms of how you organise your tasks. This requires commitment, drive and the ability to structure your work to successfully complete the doctoral thesis.

To contribute to a positive work environment and further both the department’s activities and your own development as a researcher, we expect you to be a present and active part of the day-to-day operations and workplace community.

Entry requirements and admission

To be eligible for a doctoral studentship, applicants must meet the general and specific entry requirements (Higher Education Ordinance, Chap. 7, Sect. 35).

To meet the general entry requirements, applicants must have been awarded a second-cycle qualification, satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second-cycle, or acquired substantially equivalent knowledge in some other way in Sweden or abroad (Higher Education Ordinance, Chap. 7, Sect. 39).

To meet the specific entry requirements for third-cycle studies in Computer Science, the applicant must have completed a Master’s degree (60 credits) in Computer Science, a Master’s degree (120 credits) in Computer Science or a Master of Science  degree in Computer Engineering. A person who, in some other way, in the  country or abroad, has acquired equivalent qualifications also meets  the specific entry requirements.

To be eligible for doctoral studies, the applicant must be considered to have the ability required to benefit from the programme (Higher Education Ordinance, Chap. 7, Sect. 35). Admission is based on individual assessment.

Assessment criteria

The assessment of eligible applicants is based on the criteria listed below.

Special weight will be given to:

• Research and development experience related to artificial intelligence, machine learning, large language models, or other generative AI systems.
• Experience with the design, implementation, deployment, optimization, or evaluation of AI/ML systems, or resource-constrained environments.
• Knowledge of cybersecurity, privacy, or secure systems, especially in relation to AI systems, data protection, threat modelling, or privacy-preserving technologies.
• Knowledge of methods relevant to local LLM deployment, such as fine-tuning, retrieval-augmented generation, quantization, model compression, benchmarking, or performance evaluation.

Considerable weight will be given to:

• Experience with requirement analysis, prototyping, user studies, or evaluation of digital or AI-based systems.
• Experience with interdisciplinary or collaborative research and development projects, especially involving external partners or industry.
• Good ability to work independently and systematically, including analytical, problem-solving, and organizational skills.
• Good ability to communicate research and technical results in written and spoken English. Knowledge of Swedish, or willingness to acquire Swedish language skills, is considered an advantage.

Terms

Upon admission to doctoral studies, the person will be offered the appointment of doctoral student (Higher Education Ordinance, Chap. 5, Sect. 3). The position comprises four years of full-time studies consisting of research only. If teaching or other departmental duties become relevant, the appointment will be extended by a corresponding period, up to a maximum of five years full-time. The position is fixed-term, one year initially, followed by possible extensions of a maximum of two years at a time (Higher Education Ordinance, Chap. 5). Start date as agreed by both parties.

The salary for the doctoral studentship corresponds to the standard level of salary for doctoral students and progresses in accordance with a local collective agreement.

Application

Submit the application via the university’s web-based recruitment tool, Varbi. Applicants are responsible for submitting a complete application in accordance with the advertisement, for providing translations of any documents written in a language other than Swedish, Norwegian, Danish or English, and for ensuring that the documentation allows for objective and qualitative assessments. A complete application should be submitted by the application deadline. An incomplete application may jeopardise a fair assessment of qualifications.

The application should include:

• a cover letter where the applicant details the reasons behind their interest in the position
• a list of qualifications (CV)
• degree certificate with a complete transcript of the courses included, or a certified list of completed courses with grades and dates
• copy of Master’s thesis or equivalent
• where applicable, copies of publications or certificates for other qualifications
• any letters of recommendation
• two references, such as a teacher, supervisor, or previous or current superior.

Attach all the documents and publications you wish to be considered to the electronic application (do not just provide links). Name each uploaded document to clearly indicate its content.

Documents that cannot be submitted electronically should be sent to the following address:

Karlstads universitet
HR-avdelningen
HR-administratör
651 88 Karlstad
SWEDEN

Application deadline: 2026-07-31

State the reference number: REK 2026/128

Applicants with qualifications from abroad

If you have qualifications from a university outside Sweden or if they have not been recognised by a Swedish authority before, it is important that you attach degree certificates and official transcripts to facilitate the recognition of foreign qualifications.
Provide a contact for the degree-awarding institution (phone number or email) who can verify your qualifications.

We look forward to your application!

Karlstad University has chosen advertising channels for this recruitment and firmly declines any contact with advertising or recruitment agencies.

This translation carries no legal weight.

HR Excellence in Research
Karlstad University received the European Commission’s HR Excellence in Research award September 2020. The award is issued to employers with a stimulating work environment and good conditions for researchers and its continuous improvement. The award also conveys the university’s commitment to fair and transparent recruitment as well as favorable professional development for researchers. Read more: kau.se/hrs4r

1. Stefan Alfredsson, [email protected]

1. Denita Gustavsson, OFR, [email protected]
2. Per Hurtig, SACO, [email protected]
3. Madeleine Wiker, OFR/S, Sveriges lärare, [email protected]