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

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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 projects 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 SPLAIMs industrial partners and will be carried out within the Privacy and Security (PriSec) research group at the Department of Mathematics and Computer Science.

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 departments 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.

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 Masters degree (60 credits) in Computer Science a Masters 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.

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.

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.

Submit the application via the universitys 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 Masters 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:

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!

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HR Excellence in Research
Karlstad University received the European Commissions 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 universitys commitment to fair and transparent recruitment as well as favorable professional development for researchers. Read more: