Umeå University’s Department of Applied Physics and Electronics in Sweden is currently inviting applications for a postdoctoral scholarship focused on the project Deep Learning for Real-Time Perception.
Eligible candidates must have completed a PhD in Computer Science, Electrical Engineering, or a related field, with strong expertise in Deep Learning and related areas. The scholarship is open to international applicants and provides a unique opportunity to collaborate with leading researchers in a stimulating academic environment.Umeå University is a renowned institution known for its commitment to high-quality research and education. Established in 1965, the university has grown to become one of Sweden’s leading universities, offering a wide range of undergraduate, master’s, and doctoral programs. It boasts a vibrant academic community with a strong emphasis on interdisciplinary research and innovation.
Umeå universitet Information
Founded in 1965, Umeå universitet (Umeå University) is a non-profit public higher education institution located in the suburban setting of the large town of Umeå (population range of 50,000-249,999 inhabitants), Vasterbotten County. This institution has also branch campuses in the following location(s): Örnsköldsvik, Skellefteå. Officially accredited and/or recognized by the Utbildningsdepartementet, Sverige (Ministry of Education and Research, Sweden), Umeå universitet (UmU) is a very large (uniRank enrollment range: 30,000-34,999 students) coeducational higher education institution. Umeå universitet (UmU) offers courses and programs leading to officially recognized higher education degrees in several areas of study. See the uniRank degree levels and areas of study matrix below for further details. This 54 years old higher-education institution has a selective admission policy based on students' past academic record and grades. International students are welcome to apply for enrollment.
Offered Benefits
- Conduct cutting-edge research in Deep Learning for Real-Time Perception within the context of safety-critical systems.
- Design and implement innovative algorithms and models to enhance the perception capabilities of autonomous vehicles.
- Collaborate with other team members to develop and evaluate novel approaches in real-time streaming perception, cooperative perception, and related areas.
- Publish research findings in top-tier conferences and journals.
- Present research progress and results to the research group and relevant stakeholders.
Application Process: A full application should include:
- Personal letter describing previous research experience, outlining your research interests, and how they align with the position (max 3 pages).
- Curriculum vitae (CV) with publication list.
- Copy of doctoral degree certificate or documentation clarifying when the degree is expected to be obtained.
- Copies of other diplomas, list of completed academic courses and grades.
- Copy of doctoral thesis and up to 5 relevant publications.
- Other documents that the applicant wishes to claim.
- References will be requested before a potential interview.
Submit your application as a PDF marked with the reference number FS 2.1.7-931-24, both in the file name and in the subject field of the email, to . The application can be written in English or Swedish. The application deadline is 30 June 2024.
Further Information: For more details, contact Professor Zonghua Gu ( ) and Professor Thomas Olofsson ( ).
Application Process
Applicants must submit the following required documents:
- A personal letter in which you describe previous research experience, outlining your research interests, and how they align with the position (max 3 pages)
- Curriculum vitae (CV) with publication list,
- Copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
- Copies of other diplomas, list of completed academic courses and grades,
- Copy of doctoral thesis and up to 5 relevant publications,
- Other documents that the applicant wishes to claim.
References will be requested before a potential interview.
Submit your application as a PDF marked with the reference number FS 2.1.7-931-24, both in the file name and in the subject field of the email, to .