Danica Kragic

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.

This doctoral position at KTH Royal Institute of Technology offers an exciting opportunity to join the EU project "Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors." The project aims to digitalize the sense of smell, advance understanding of olfactory perception in humans, and develop AI models that replicate these processes. Two PhD positions are available, each focusing on different aspects: one on time series data (EEG), signal processing, and machine learning; the other on computer vision, machine learning, and video processing. Supervision will be provided by Professor Danica Kragic, a leading expert in the field. The research environment at KTH is dynamic and international, with a strong emphasis on innovation, sustainability, and interdisciplinary collaboration. As a doctoral student, you will benefit from attractive working conditions, employee benefits, and a monthly salary according to KTH’s doctoral student salary agreement. Eligibility requires a second cycle degree (master's or equivalent), or completion of at least 240 higher education credits (including 60 at the second cycle), or equivalent knowledge. English proficiency equivalent to English B/6 is mandatory. Candidates should demonstrate experience in machine learning, signal processing, time series analysis (EEG), computer vision, and video processing. Selection criteria include independence, collaboration skills, professional approach, and analytical ability, with personal skills highly valued. The position is full-time, temporary, and can last up to four years. Doctoral students may perform limited additional tasks (up to 20%) such as training and administration. Employment is initially for one year, with possible renewals. Security clearance may be required for certain roles. KTH values equality, diversity, and equal opportunities, and offers a creative and supportive environment for academic growth. To apply, submit your application via KTH's recruitment system. Required documents include diplomas, grades, certificates of language proficiency, CV, application letter (max 2 pages), and representative publications or technical reports (with summaries and web links for longer documents). Applications must be complete and received by the deadline: May 27, 2026. For further information, contact Professor Danica Kragic at [email protected]. Join KTH and contribute to cutting-edge research in machine learning, AI, and olfactory perception.