Target degree: Doctor of Science (Technology)
Study time: Four years (when studying full-time)
Supervisor: Prof. Yu Xiao (mobilecloud.aalto.fi)
Starting date: August 1st, 2019
Site of Research: Mobile cloud computing group (mobilecloud.aalto.fi), School of Electrical Engineering, Aalto University
Research areas: Deep learning
Optional topics: deep video analytic, AI-driven edge computing, deep learning for mobility analytic
We are looking for doctoral students to work for the 5G-MOBIX (5G for cooperative & connected automated mobility on x-border corridors) project. Funded by the European Commission, 5G-MOBIX applies and evaluates 5G core technological innovations to autonomous driving use cases across cross-border and urban test sites around Europe and Asia. The industry consortium includes about 100 partners from telecom (e.g. Telefonica, China Mobile, Nokia, etc.) and automotive (e.g. Ford, Daimler, Sinotruck, etc.), plus public authorities.
The candidate must have a master’s degree (or equivalence) in electrical engineering, computer science, mechanical engineering, cognitive science or in a related study with excellent results. The candidate must have a high motivation for research, and enjoy working in an international and cross-disciplinary team.
For the candidate qualified for the current position, an official Aalto University application process for doctoral studies will be accomplished. Hence, before preparing his/her application for the current call a candidate should ensure that the corresponding formal requirements will be fulfilled: https://into.aalto.fi/display/endoctoralelec/How+to+apply#Howtoapply-granting
Skills and qualities required to apply
Please submit your application through our recruiting system by using "Apply now!" link below, no later than May 15, 2019. Please include the following documents in English:
Further information: Assistant Professor Yu Xiao, firstname.lastname@example.org (research related information) and HR Coordinator Katja Korpinurmi email@example.com (application process, practical arrangements)
About Aalto University and Finland
Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto University has been ranked the 9th best young university in the world (Top 50 under 50, QS 2018) and one of the world’s top technology challenger universities (THE 2017), for its outside-the-box thinking on research collaboration, funding and innovation. Aalto has six schools with nearly 11 000 students and 4000 employees of whome close to 400 are professors. Our campuses are located in the capital area of Finland. With 37% of our academic faculty coming from outside Finland, we are a highly international community with strong academic standing.
At Aalto, high-quality research, art, education and entrepreneurship are promoted hand in hand. Disciplinary excellence is combined with multidisciplinary activities, engaging both students and the local innovation ecosystem. Our main campus is quickly transforming into an open collaboration hub that encourages encounters between students, researchers, industry, startups and other partners. Aalto University was founded in 2010 as three leading Finnish universities, Helsinki University of Technology, the Helsinki School of Economics and the University of Art and Design Helsinki, were merged to strengthen Finland’s innovative capability.
As a living and work environment, Finland consistently ranks high in quality-of-life. For more information about living in Finland, please visit our information pages for international staff: https://www.aalto.fi/aalto-university/international-staff-guideApprenez-en davantage
|Title||2 Doctoral Candidate Positions in the area of Deep Learning|
|Job location||Lämpömiehenkuja 2, 02150 Espoo|
|Published||mars 20, 2019|
|Application deadline||mai 15, 2019|
|Job type||PhD  |
|Fields||Algorithmes,   Statistiques,   Intelligence artificielle,   Réseau de neurones artificiels,   Extraction de données,   Mathématiques appliquées,   Mathématiques informatiques,   Apprentissage automatique,   Vision industrielle,    and 1 more. Vision par ordinateur  |