PhD in Models, Algorithms, and Optimization for Machine Learning at KTH and NTU KTH Royal Institute of Technology in Sweden

KTH Royal Institute of Technology is advertising a fully funded PhD position in models, algorithms, and optimization for machine learning, leading to a joint doctoral degree from KTH (Sweden) and Nanyang Technological University (Singapore).

The project is broadly situated in computer science and machine learning, with possible research directions including algorithmic knowledge discovery, graph mining, social network analysis, optimization for machine learning, representation learning, and fair, accountable, and transparent machine learning. The doctoral student will be recruited and formally enrolled at KTH and will spend at least 12 months at NTU in Singapore as part of the joint program.

Supervision is proposed by Professor Aristides Gionis (KTH), Assistant Professor Sebastian Dalleiger (KTH), and Associate Professor Kelly Ke Yiping (NTU).

Eligibility highlights include a Master of Science degree by enrollment time, or equivalent qualifying credits/knowledge, plus English B/6 or equivalent. The call also emphasizes strong academic credentials, a solid background in algorithms design, machine learning, and optimization, along with strong programming and implementation skills.

Funding is described as a monthly salary according to KTH’s doctoral student salary agreement, with standard employee benefits. This is a doctoral employment rather than a scholarship.

Deadline: 25 June 2026. Applications must be submitted through KTH’s recruitment system and include diplomas, transcripts, proof of language requirements, CV, a motivation/application letter, and representative publications or technical reports.