This fully funded PhD position at KTH Royal Institute of Technology is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest research initiative in artificial intelligence and autonomous systems. The successful candidate will join the new research group led by Assistant Professor Martin Trapp, with co-supervision by Professor Henrik Boström, to focus on the reliability and trustworthiness of machine learning models.

The project involves working with open-source, large-scale machine learning models, developing new theoretical and methodological approaches to enhance their reliability, and contributing to open-source libraries. The research aims to publish in top-tier machine learning conferences such as NeurIPS, ICML, ICLR, UAI, and AISTATS. The WASP program offers a dynamic, international research environment with opportunities for collaboration with industry and leading universities worldwide. The graduate school provides a comprehensive training program, including research visits, partner university collaborations, and lectures from visiting scholars, fostering a strong interdisciplinary and international network.

The position is based in Stockholm and comes with a monthly salary according to KTH’s doctoral student salary agreement. Applicants must have a master’s degree or equivalent, strong mathematical and programming skills, a background in machine learning, statistics, linear algebra, and optimization, and some research experience evidenced by peer-reviewed publications. Proficiency in English (equivalent to English B/6) is required.

The position is full-time, initially for one year with possible extensions, and is open to candidates who are goal-oriented, independent, and collaborative. Applications must be submitted through KTH’s recruitment system by December 19, 2025, and should include certified academic transcripts, proof of language proficiency, a CV, a research statement, an application letter, and a list of publications.

The position offers excellent working conditions, employee benefits, and the chance to contribute to cutting-edge research in trustworthy AI.