This PhD position at KTH Royal Institute of Technology is part of a prestigious, five-year Wallenberg Scholar project titled "Scalable and adaptive inferencing for democratizing AI." The project, with a budget of 18 million SEK, aims to dramatically reduce the cost and energy required to serve large language models such as ChatGPT. The research will focus on the design, implementation, and evaluation of distributed systems and networks for machine learning inference, as well as the application of machine learning concepts to develop agent-based frameworks. The successful candidate will join a dynamic, international research environment, collaborating with industry and leading universities worldwide. The position offers full-time employment with a monthly salary according to KTH's doctoral student salary agreement, along with a range of employment benefits. The doctoral studies are expected to be completed within four years, with the possibility of limited teaching or administrative duties (up to 20%). Supervision will be provided by Professor Dejan Kostic and Universitetslektor Marco Chiesa, both recognized experts in the field. The research will be conducted within the School of Electrical Engineering and Computer Science at KTH, in Stockholm, Sweden. Eligibility: Applicants must have a master's degree or equivalent in a relevant field, or have completed at least 240 ECTS credits (with at least 60 at the advanced level). Proficiency in English equivalent to English B/6 is required. A strong background in computer science, engineering, or machine learning is expected, and knowledge of systems and networking is highly meritorious. The selection process will emphasize personal qualities such as goal orientation, persistence, independence, collaboration skills, and the ability to analyze and address complex problems. Application Process: Applications must be submitted via the KTH recruitment system by January 15, 2026 (midnight CET/CEST). Required documents include a CV, cover letter (max 2 pages), degree certificates and transcripts, proof of language proficiency, and representative publications or technical reports. Documents not in English or Swedish must be translated. For more information about the project, visit the project blog . For application, use the official application link . KTH is committed to equality, diversity, and good working conditions. The university plays a leading role in education, research, and innovation, and offers a creative and dynamic workplace. For further inquiries, contact Professor Dejan Kostic (dmk@kth.se) or Universitetslektor Marco Chiesa (mchiesa@kth.se).