Doctoral student in models, algorithms, and optimization for machine learning
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 will 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 broadly situated within computer science, focusing on advanced machine learning topics such as 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 computational sciences, applied mathematics, and statistics, and who are eager to contribute to cutting-edge research in these areas.
Applicants must hold or be about to receive a Master of Science degree in computer science, machine learning, AI, data science, or a related field. Alternatively, candidates may qualify with at least 240 higher education credits, including 60 at the second-cycle level, or equivalent knowledge. English proficiency equivalent to English B/6 is mandatory. The selection process emphasizes academic excellence, strong background in algorithms, machine learning, optimization, programming skills, and personal attributes such as goal orientation, perseverance, independence, collaboration, and professional approach.
The position is fully funded, offering a monthly salary according to KTH’s doctoral student salary agreement, along with employee benefits and a supportive workplace environment. The employment is temporary, full-time, and may be renewed according to KTH regulations. The doctoral student will have access to a creative and dynamic research environment, with opportunities for professional growth and development.
To apply, candidates must submit their application through KTH's recruitment system, ensuring all required documents are included: CV, application letter, diplomas, grades, certificates of language requirements, and representative publications or technical reports. Applications must be received by the deadline of March 5, 2026. For further information, contact Professor Aristides Gionis ([email protected]).
KTH Royal Institute of Technology is a leading international technical university, committed to advancing education, research, and innovation for a sustainable society. The university values equality, diversity, and equal opportunities, providing an inclusive environment for all students and staff.
