Danica Kragic
Top university
5 months ago
This position has expired. You can find similar positions from the section below or browse our positions listing pages.
Doctoral student in Machine Learning KTH Royal Institute of Technology in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
Sweden
University
KTH Royal Institute of Technology
How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Suggested positions
Keywords
About this position
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.
Funding details
Available
What's required
Applicants must have a second cycle degree (master's degree or equivalent), or have completed at least 240 higher education credits, including at least 60 second-cycle credits, or possess substantially equivalent knowledge. Mandatory requirement for English proficiency equivalent to English B/6. Candidates should have experience in machine learning, signal processing, time series data (EEG), computer vision, and video processing. Selection is based on ability to work independently, collaborate, professional approach, and analytical skills. Personal skills are highly valued. Security clearance may be required for some positions.
Ask ApplyKite AI
Professors
How do I apply for this?
Sign in for free to reveal details, requirements, and source links.