This fully funded PhD position at KTH Royal Institute of Technology in Stockholm, Sweden, is part of the EU MSCA Doctoral Network ELEVATE, focusing on neuromorphic event-based sensing and computation for low-power, low-latency applications. The project centers on sensory perception for closed-loop robotic systems, specifically event vision for human-robot co-working scenarios. Traditional convolutional neural networks for computer vision require significant computational resources and introduce latency, even with modern GPUs. This research aims to overcome these limitations by investigating neuromorphic sensors and sensor fusion using multiple event-cameras in real-time human-robot collaborative environments. The robotic platform features a 7 DOF manipulator interacting with humans and various tools, providing a rich testbed for advanced perception and control.

The doctoral student will be based at KTH, with mandatory research stays (secondments) at partner universities and companies across Europe, offering a unique opportunity for international collaboration and exposure. The position is supervised by Prof. Dr. Jörg Conradt and co-supervised by Prof. Dr. Arvind Kumar, both leading experts in neuromorphic computing and robotics. Funding is secured through a combination of KTH resources (up to 1 year) and the EU MSCA DN ELEVATE program (up to 3 years), including a competitive monthly salary (starting at 33,000 SEK, approx. 2,991 EUR), mobility allowance, and possible family allowance as per Marie Curie regulations.

Eligibility requirements include compliance with the EU Mobility Rule (no more than 12 months residence/activity in Sweden in the past 3 years), a second cycle degree (master's or equivalent), or at least 240 higher education credits (with 60 at second-cycle level), and English proficiency equivalent to English B/6. Ideal candidates will have expertise in neuromorphic/event-based vision processing, robotics (hardware/software), strong programming skills (including C), and experience in neural networks or machine learning. Selection emphasizes personal qualities such as independence, collaboration, professionalism, and analytical skills.

Employment is full-time and temporary, with a maximum duration corresponding to four years of full-time doctoral education. Doctoral students at KTH benefit from a dynamic, creative research environment, attractive employee benefits, and opportunities for professional growth. The university values equality, diversity, and inclusion as core principles. Security clearance may be required for certain roles.

To apply, candidates must submit a complete application via KTH's recruitment system, including a CV, application letter (max 2 pages), certified copies of diplomas and grades, language certificates, and representative publications or technical reports. Translations into English or Swedish are required if documents are not in these languages. Applications must be received by midnight CET on 2026-01-09. For further details, contact Prof. Dr. Jörg Conradt at [email protected].