Doctoral student in models, algorithms, and optimization for machine learning KTH Royal Institute of Technology in Sweden

This fully funded doctoral position at KTH Royal Institute of Technology offers an exciting opportunity to pursue a joint PhD degree in models, algorithms, and optimization for machine learning, in collaboration with Nanyang Technological University (NTU), Singapore. The successful candidate will be formally enrolled at KTH and spend at least 12 months at NTU as part of the joint program, benefiting from supervision by Professor Aristides Gionis (KTH), Associate Professor Kelly Ke Yiping (NTU), and Assistant Professor Sebastian Dalleiger (KTH).

The research project is situated within the broad field of machine learning, with potential topics including algorithmic knowledge discovery, graph mining, social network analysis, optimization for machine learning, representation learning, and fair, accountable, and transparent machine learning. The position is ideal for candidates with a strong interest in advancing the theoretical and practical aspects of machine learning and computational sciences.

Applicants must hold or be about to receive a Master of Science degree in computer science, machine learning, AI, data science, or a related area. Essential qualifications include a solid background in algorithm design, machine learning, and optimization, as well as strong programming and implementation skills. English proficiency equivalent to English B/6 is mandatory. Candidates should demonstrate strong academic credentials, excellence in coursework or relevant projects, and personal skills such as goal orientation, perseverance, independence, collaboration, professionalism, and the ability to analyze complex issues.

The position is fully funded, with a monthly salary according to KTH’s Doctoral student salary agreement, and includes employee benefits and a workplace at KTH. The doctoral student will be employed for a maximum of one year initially, with possible renewals up to four years in total. The role may include up to 20% training and administrative tasks. The research environment at KTH is creative and dynamic, offering opportunities for growth and development, and is committed to equality, diversity, and sustainability.

To apply, candidates must submit their application through KTH's recruitment system, including diplomas, grades, certificates of language requirements, CV, application letter, and representative publications or technical reports. Certified translations are required if documents are not in English or Swedish. Applications must be received by the closing date of June 25, 2026. For further information, contact Professor Aristides Gionis ([email protected]).

This position provides a unique opportunity to work at the intersection of machine learning, algorithms, and optimization, and to earn a joint PhD degree from two leading international technical universities. Join KTH and NTU to shape the future of machine learning research!