DTU Management’s Transport Division invites applications for a 3-year PhD position in the field of computer vision, edge computing, federated learning, and road safety. The successful candidate will join the Transport Psychology Group and will work under the supervision of Assistant Professor Felix Siebert, Senior Researcher Mette Møller, and Professor Francisco Pereira.The PhD project will investigate privacy-preserving detection of safety-related behaviour of road users in the road environment, with computer vision and federated learning. Relevant data will be collected in road environments in Denmark and Singapore. State-of-the-art object detection approaches will be applied on the collected data. Detection robustness and privacy-preserving features, including edge computing and federated learning, will be developed. Collected behavioural data will be used to identify patterns of safe and unsafe behaviour of road users, within the scopes of short- and long-term trends. The project is a strategic collaboration between the Technical University of Denmark (DTU) and its Alliance Network partner Nanyang Technological University (NTU) and will be conducted under the DTU-NTU double degree framework agreement which offers the opportunity to receive PhD diplomas from both DTU (home institution) and NTU (host institution). Your PhD study will include a 1-year stay at NTU. You will be a member of the Transport Psychology section at the Department for Technology, Management and Economics (DTU Management) at the Technical University of Denmark. You will work under the supervision of Senior Researcher Mette Møller, Professor Francisco Pereira (Machine Learning for Smart Mobility section), and Assistant Professor Felix Siebert. Further supervision is provided by Professor Dusit Niyato from the School of Computer Science and Engineering (SCSE) at NTU. Responsibilities and qualificationsYour primary tasks will be to Plan and conduct systematic roadside video data collection in Denmark and Singapore Based on the collected data, develop, test, and apply object detection approaches for safety related behaviour Advance the state of the art in edge computing and/or federated learning to facilitate data privacy Analyse the collected road user data for behavioural patterns Write academic papers aimed at high-impact journals Participate in international conferences and workshops Disseminate research results and teach as part of the overall PhD education You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree. Specifically, we seek applicants with a master’s degree in transport, mathematics, statistics, computer science, civil engineering, industrial engineering, or a related discipline. We are looking for an ambitious, self-organized individual with strong project management and communication skills. Applicants should have experience in some of the following areas: computer vision, federated learning, edge computing, statistics, machine learning, data collection, and analysis. Programming skills in Python or similar and proficient English language skills are also required.