DTU Management’s Transport Division invites applications for a 3-year Ph.D. 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 Ph.D. project will investigate the privacy-preserving detection of safety-related behavior 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 to the collected data. Detection robustness and privacy-preserving features, including edge computing and federated learning, will be developed. Collected behavioral data will be used to identify patterns of safe and unsafe behavior 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 Ph.D. diplomas from both DTU (home institution) and NTU (host institution). Your Ph.D. 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 qualifications
Your 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 behavior
- Advance the state of the art in edge computing and/or federated learning to facilitate data privacy
- Analyze the collected road user data for behavioral 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 Ph.D. 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.
Approval and Enrolment
The scholarship for the Ph.D. degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programs at DTU. For information about our enrolment requirements and the general planning of the Ph.D. study program, please see DTU's rules for Ph.D. education.
Assessment
The review of applications will begin on 8 September 2022.
We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation, and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. The preferred starting date is 1 January 2023. The position is a full-time position.
You can read more about career paths at DTU here.
Workplace
This Ph.D. study is under the Double Doctorate Degree agreement between DTU and NTU. DTU will be the home institution that will handle all the administrative and financial aspects of joint education. DTU will enroll the candidate in one of its Ph.D. programs and nominate the main supervisor. NTU will be the host institution and will also enroll the candidate in one of its Ph.D. programs. The candidate must spend a minimum of one year at each of the two institutions.
Further information
Further information may be obtained from Assistant Professor Felix Siebert ([email protected]).
You can read more about DTU Management at www.man.dtu.dk/english.
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “Ph.D. relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a Ph.D. at DTU.
Application procedure
Your complete online application must be submitted no later than 7 September 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma (in English) including an official description of the grading scale
You may apply before obtaining your master's degree but cannot begin before having received it.
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, race, disability, religion, or ethnic background are encouraged to apply.