卡尔斯塔德大学PhD position in Computer Science with a focus on AI and cybersecurity申请条件要求-申请方
主办方
卡尔斯塔德大学
PhD直招介绍
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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.
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.
卡尔斯塔德大学Phd申请条件和要求都有哪些？PhD position in Computer Science with a focus on AI and cybersecurity项目是不是全奖？有没有奖学金？下面我们一起看一下卡尔斯塔德大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
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.
报名方式
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招生人信息
Stefan Alfredsson
邮箱：stefan.alfredsson@kau.se
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