BEMÆRK: Ansøgningsfristen er overskredet
Applicants are invited for two PhD fellowships/scholarships at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The positions are available from 01 May 2024 or later. You can submit your application via the link under 'how to apply'.
Title:
Deep Learning for Artificial Intelligence of Things
Research area and project description:
We invite applications for two PhD positions financed by the Horizon Europe project PANDORA and the NordForsk project Nordic University Cooperation on Edge Intelligence (NUEI). The two selected candidates will have good opportunities to work, interact, and network with researchers, scientists, and engineers working in European Universities, Research Institutes, and Companies forming its consortium. In addition, the PhD candidate has opportunities to participate in the summer schools and PhD courses in NUEI.
The first PhD project aims to propose new Deep Learning models for efficient inference of Artificial Intelligence of Things (AIoT) input streams. Such streams can be collected by sensors (e.g., image sequences and sensor time-series) and will be processed in real time. We will build on our recently introduced Continual Inference Networks, which comprise the Continual 3D Convolutional Neural Networks, the Continual Transformer Encoders, and the Continual Spatio-Temporal Graph Convolutional Networks, for enabling the construction of highly optimised inference pipelines that can execute complex models with low latency and high throughput.
The second PhD project aims at developing novel techniques for distributed AI learning and inferencing in the IoT-Edge-Cloud continuum. The project aims to efficiently manage the trade-off between resource utilisation, and inference accuracy, time and energy consumption across the continuum, by adapting to the dynamic changes in the communication networks and data processing environment. We will propose and develop novel algorithms for dynamic workload distribution, load balancing, and energy management, to optimise AI learning and inferencing in the IoT-Edge-Cloud continuum.
As part of the two PhD projects, the selected candidates will interact with the collaborators in the two projects, perform knowledge dissemination, e.g., through conference participation and project reporting to present their work, and have the opportunity to participate in activities of the two projects.
Project description (½-4 pages). This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found.
Qualifications and specific competences:
Applicant for the two PhD positions must have:
- Master’s degree in Computer Engineering, Computer Science, or within a relevant area.
- Background on machine learning is required.
- Strong programming skills, especially Python programming, is required.
- Excellent English verbal and written skills.
- Be able to work well and communicate expert knowledge in an interdisciplinary team.
- Background in video processing, deep learning, or wireless communications is a plus.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Helsingforsgade 10, 8200 Aarhus N, Denmark for one of the PhD positions and Finlandsgade 22, 8200 Aarhus N, Denmark for the other PhD position.
Contacts:
Applicants seeking further information are invited to contact:
- Professor Alexandros Iosifidis, ai@ece.au.dk (main supervisor for one PhD student and co-supervisor for the other PhD student)
- Associate Professor Qi Zhang, qz@ece.au.dk (main supervisor for one PhD student and co-supervisor for the other PhD student)
How to apply:
Please follow this link to submit your application.
Application deadline is 15 February 2024 23:59 CET.
Preferred starting date is 01 May 2024.
For information about application requirements and mandatory attachments, please see our application guide.
Please note:
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
INFORMATIONER OM STILLINGEN:
- Arbejdspladsen ligger i:
Aarhus Kommune
-Virksomheden tilbyder:
-Arbejdsgiver:
Aarhus Universitet, Nordre Ringgade, 8000 Aarhus C
-Ansøgning:
Ansøgningsfrist: 01-02-2024; - ansøgningsfristen er overskredet
Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5955600