Doctoral Students in Machine Learning – Digitising Smell Project

The KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for two doctoral student positions in Machine Learning as part of the EU project "Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors." This innovative project aims to digitalize the sense of smell, advance our understanding of olfactory perception in humans, and develop AI models that replicate these processes. The research will contribute to both fundamental neuroscience and applied computational sciences, with a focus on signal processing, machine learning, and computer vision. PhD student 1 will work with time series data (EEG), signal processing, and machine learning to explore the neural basis of olfactory perception. PhD student 2 will focus on computer vision, machine learning, and video processing to model and analyze the digital transmission of odors. Both positions offer the opportunity to engage in cutting-edge interdisciplinary research at the intersection of artificial intelligence and human sensory systems. Supervision will be provided by Professor Danica Kragic, a leading expert in the field. The positions are full-time and based at KTH Royal Institute of Technology, a renowned technical university known for its creative and dynamic research environment. The employment is temporary, with a contract duration corresponding to four years of full-time doctoral education. Monthly salary is provided according to KTH’s doctoral student salary agreement, along with attractive employee benefits and a supportive workplace. Eligibility requirements include a second cycle degree (such as a master's degree) or equivalent, proficiency in English (English B/6), and relevant experience in machine learning, signal processing, computer vision, EEG, or video processing. Selection will be based on academic qualifications, personal skills, and the ability to work independently and collaboratively. Security clearance may be required for certain positions. To apply, candidates must submit a complete application through KTH's recruitment system by the deadline of March 5, 2026. Required documents include a CV, application letter outlining research interests and motivation, certified copies of diplomas and grades, proof of language proficiency, and representative publications or technical reports. Translations into English or Swedish are required if documents are not originally issued in these languages. KTH is committed to equality, diversity, and equal opportunities, and offers a stimulating environment for doctoral studies. Join us in shaping the future of research and innovation in machine learning and olfactory perception.