PhD Position in Machine Learning for Robotic Manipulation KTH Royal Institute of Technology in Sweden

This PhD position at KTH Royal Institute of Technology is focused on advancing machine learning methods for robotic manipulation. The successful candidate will join the research group led by Lektor Florian Pokorny, which specializes in developing data-driven approaches for enabling robots to acquire new manipulation skills. The project aims to integrate large-scale, real-world robotic manipulation experiments and benchmarking into a robust, statistically reliable pipeline, leveraging the lab's CloudGripper platform—a remote-access, cloud robotics infrastructure featuring a variety of robot arm work cells.

A key component of the project is the establishment of internationally relevant, large-scale datasets and benchmarks for robotic manipulation, providing a reliable foundation for future research in the field. The research environment is dynamic and international, with opportunities for collaboration with industry and leading universities worldwide. The position offers a full-time, fixed-term employment contract for up to four years, with a monthly salary according to KTH's doctoral student agreement and a range of employment benefits.

Eligibility requirements include a completed advanced degree (Master's or equivalent) or at least 240 ECTS credits (with at least 60 at the advanced level), or equivalent knowledge acquired in another way. Proficiency in English equivalent to English B/6 is mandatory. Selection criteria emphasize the ability to work independently, collaborate effectively, maintain a professional approach, and analyze complex problems. Personal qualities are highly valued in the selection process.

Applicants must submit a complete application via the KTH recruitment system, including a CV, a motivation letter (maximum two pages) outlining academic interests and motivation for doctoral studies, and representative publications or technical reports. The application deadline is November 28, 2025 (midnight CET/CEST). For further information, contact Florian Pokorny at [email protected].

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