This doctoral student position at KTH Royal Institute of Technology is part of a major 5-year Wallenberg Scholar project titled “Scalable and adaptive inferencing for democratizing AI,” with a total funding of 18 Million SEK. The project aims to dramatically reduce the cost and energy consumption associated with serving large language models, such as ChatGPT, making advanced AI more accessible and sustainable. The research will focus on the design, implementation, and evaluation of distributed systems and networks for machine learning inference, as well as the development of agentic frameworks to enhance AI capabilities. Supervision will be provided by Professor Dejan Kostic and Associate Professor Marco Chiesa, both experts in computer science and systems research. The successful candidate will join a dynamic, international research environment, collaborating with industry partners and leading universities worldwide. The position offers full-time employment for up to four years, with a monthly salary according to KTH’s doctoral student salary agreement and access to employee benefits. Applicants must hold a master’s degree or equivalent, or have completed at least 240 higher education credits (with at least 60 at the second-cycle level). English proficiency equivalent to English B/6 is mandatory. The selection process values goal orientation, perseverance, independence, collaboration skills, and the ability to analyze complex issues. Candidates from computer science, engineering, data science, and machine learning backgrounds are encouraged to apply, with knowledge of systems and networking considered highly desirable. Applications must include a CV, application letter, diplomas and grades, language certificates, certified translations if necessary, and representative publications or technical reports. The application deadline is January 15, 2026. For more information about the project and early publications, visit the project page. KTH is committed to equality, diversity, and providing a creative and supportive environment for research and personal development.