Marco Chiesa

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.

This doctoral student position at KTH Royal Institute of Technology is part of the ambitious Wallenberg Scholar project, 'Scalable and adaptive inferencing for democratizing AI', with a total funding of 18 Million SEK. The project aims to significantly reduce the cost and power consumption for serving large language models such as ChatGPT, focusing on the design, implementation, and evaluation of distributed systems and networks for machine learning inference. The research will also explore agentic frameworks and scalable, adaptive AI systems. Supervision will be provided by Professor Dejan Kostic and Associate Professor Marco Chiesa. The position is based in Stockholm, Sweden, and offers full-time employment for up to four years, with a monthly salary according to KTH's doctoral student salary agreement and a range of employee benefits. The work environment at KTH is creative and dynamic, with a strong emphasis on equality, diversity, and opportunities for professional growth. Applicants must have a second cycle degree (such as a master's) or equivalent, or 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 scientific curiosity, perseverance, independence, collaboration, 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 highly desirable. To apply, candidates must submit certified copies of diplomas and grades, proof of language requirements, a CV, an application letter (maximum 2 pages), and representative publications or technical reports. Applications must be submitted via KTH's recruitment system by the deadline of May 17, 2026. The position may require a security clearance in accordance with Swedish law if classified as security-sensitive. KTH firmly declines contact with staffing and recruitment agencies. This opportunity is ideal for students seeking to contribute to cutting-edge research in scalable AI, distributed systems, and large language model inference, within a leading international technical university.

The KTH Royal Institute of Technology invites applications for a doctoral student position in Large Language Model inferencing, as part of the ambitious Wallenberg Scholar project “Scalable and adaptive inferencing for democratizing AI.” This five-year, 18 Million SEK project aims to dramatically reduce the cost and power requirements for 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. The project also involves applying machine learning concepts to develop agentic frameworks, with the goal of advancing scalable and adaptive AI technologies. The position is supervised by Professor Dejan Kostic and Associate Professor Marco Chiesa, both leading experts in distributed systems and networking. Applicants should have a strong background in computer science, engineering, data science, or machine learning. Knowledge of systems and networking is highly desirable. The position requires a second cycle degree (such as a master's) or equivalent, or at least 240 higher education credits (with at least 60 at second-cycle level). English proficiency equivalent to English B/6 is mandatory. Candidates will be assessed on their ability to work independently, collaborate effectively, and analyze complex issues. Scientific curiosity and a desire to tackle challenging, relevant problems are highly valued. The doctoral student will be employed full-time for up to four years, with a monthly salary according to KTH’s Doctoral student salary agreement and access to employee benefits. The position offers a creative and dynamic research environment at one of Europe’s leading technical universities, with opportunities for professional growth and development. Equality, diversity, and equal opportunities are integral to KTH’s core values. To apply, candidates must submit a complete application through KTH’s recruitment system, including certified copies of diplomas and grades, proof of language requirements, CV, application letter (maximum two pages), and representative publications or technical reports. Applications must be received by the deadline, 2026-04-30. For further information about doctoral studies at KTH and the project, please refer to the official KTH website and project page. Join KTH and contribute to cutting-edge research in scalable and adaptive AI inferencing, helping to shape the future of technology and society.

This postdoctoral position at KTH Royal Institute of Technology is part of the Wallenberg Scholar project "Scalable and adaptive inferencing for democratizing AI," with a substantial budget of 18 Million SEK. The project aims to significantly reduce the cost and power consumption for serving large language models, such as ChatGPT, by advancing scalable and adaptive inferencing techniques. The research will focus on the design, implementation, and evaluation of distributed systems and networks for machine learning inference, including the development of agentic frameworks. As a postdoc, you will join a dynamic research lab, collaborating with faculty members and doctoral students, and contribute to both scientific publications and new grant applications. The position is supervised by Professor Dejan Kostic and Associate Professor Marco Chiesa, offering opportunities for experimental systems work and interdisciplinary collaboration. The ideal candidate will have a strong background in distributed systems, networking, programming, and operating systems, with proficiency in C++, Python, Linux, and scripting languages. Experience with machine learning, GPU programming, or large-scale inference systems is highly valued. The role requires excellent English communication skills, critical thinking, and a willingness to experiment and explore new ideas. Awareness of diversity and equal opportunity issues, particularly gender equality, is also important. KTH is a leading international technical university located in Stockholm, Sweden, known for its commitment to education, research, and innovation. The university provides a creative and dynamic environment, attractive benefits, and good working conditions. The postdoctoral appointment is full-time, temporary (up to two years), and offers a monthly salary. Applicants must submit a complete application, including CV, diplomas, grades, translations if necessary, and a brief statement of research interests and goals. The deadline for applications is May 25, 2026. This position is ideal for candidates seeking to advance their research career in AI, distributed systems, and scalable machine learning inference, while contributing to a high-impact project at a renowned institution.

This postdoctoral position at KTH Royal Institute of Technology is part of the prestigious Wallenberg Scholar project, "Scalable and adaptive inferencing for democratizing AI," with a total funding of 18 Million SEK. The project aims to significantly reduce the cost and power consumption associated with serving large language models, such as ChatGPT, making advanced AI more accessible and sustainable. The successful candidate will focus on the design, implementation, and evaluation of distributed systems and networks for machine learning inference, contributing to the development of agentic frameworks and experimental systems. The research will be conducted in a collaborative environment alongside faculty members, including Professor Dejan Kostic and Associate Professor Marco Chiesa, as well as several doctoral students. The postdoc will be expected to contribute to scientific publications and new grant applications, and will have opportunities to engage in experimental systems work. The position is full-time, based in Stockholm, and is offered for up to two years with a competitive monthly salary. Applicants must hold a doctoral degree (or equivalent foreign degree) by the time of employment and possess a strong background in distributed systems, networking, programming, and operating systems. Proficiency in English, C++, Python, Linux, and scripting languages is required. Preferred qualifications include recent doctoral graduation (within three years), teaching abilities, awareness of diversity and equal opportunity issues, and experience with machine learning, GPU programming, or large-scale inference systems. The ability to work both independently and collaboratively is essential, and international publications are highly valued. KTH offers a dynamic and creative research environment with excellent working conditions and benefits. The university is committed to equality, diversity, and equal opportunities, which are integral to its core values. The application process requires submission of a CV, diplomas and grades (with translations if necessary), and a brief statement of research interests and goals. Applications must be submitted through KTH's recruitment system by June 21, 2026. For further information, contact Professor Dejan Kostic ([email protected]) or Associate Professor Marco Chiesa ([email protected]). For application, visit the official link provided.