TITLE OF POST:
|Title of Post |PhD Researcher in Computer Networks |
|Reports to |Dr. Brian Lee, Dr. Yuansong Qiao |
|Project Area |Programmable Communication Infrastructure for Smart Manufacturing |
|Post Duration (Months) |48 Months |
|Third Level Institute & Faculty |Software Research Institute, Athlone Institute of Technology |
|Internal Confirm Collaborator(s) |TBC |
|Work Package # |WP2.1-4 |
|ID REF #: | |
|Deadline for Applications |Rolling deadline until the vacancy is filled |
|SALARY SCALE: |SFI Defined Scale |
JOB DESCRIPTION
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|OVERVIEW: |
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|The Confirm Centre for Smart Manufacturing is a new research centre based at the University of Limerick with partner institutions Tyndall National |
|Institute, University College Cork, Cork Institute of Technology, NUI Galway, Maynooth University, Athlone Institute of Technology and Limerick Institute|
|of Technology. The Centre, which is funded by Science Foundation Ireland with co-funding from industry, brings together 42 industry partners and 16 |
|international manufacturing centres of excellence to focus on the development of smart manufacturing for applications across Ireland’s leading industrial|
|sectors. Confirm’s ambition is to become a world leader in smart manufacturing research and to enable Irish industry to fundamentally transform to a |
|smart manufacturing ecosystem, delivering measurable and visible economic impact to Ireland. The successful candidate will work with a world-class team |
|of academics, researchers and industry partners in a highly innovative and motivated environment. |
| |
|The current position is for a full-time PhD programme aiming to develop a Knowledge Centric Networking framework for smart manufacturing environments, |
|with special focus on developing in-network programming / computation models to support diverse distributed AI/robotics systems. |
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|The number of devices connected by the Internet of Things (IoT) will be steadily growing and reaching 50 billion by 2020. With the booming of machine |
|learning, intelligent agents and robots will play important roles in the IoT era, which will interact with the large volume of sensors and actuators to |
|create diverse distributed artificial intelligence (AI) applications in helping the society, e.g. smart manufacturing, smart city, and smart |
|transportation. For example, in smart city scenarios, a trend is to deploy distributed machine learning algorithms to process the large volume of data |
|from devices, which has led to a new smart city concept, i.e. city brain. In this scenario, various sensors, e.g. noise sensors, cameras and air |
|pollution sensors, act as listening, visual, feeling systems of the city, various actuators, e.g. traffic lights, robots, home devices, and manufactural |
|devices, act as the motion system, and the edge and cloud will act as the inference and decision system. |
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|These distributed AI/robotics applications will be deployed across the Internet by exploring the capabilities of devices, edge and cloud, gathering |
|information from a large quantity of sensors and generating knowledge from the sensed data. The acquired knowledge from distributed smart agents will be |
|further exchanged and composed to create high level learning and inference systems. The learnt knowledge will form the foundation of distributed |
|inference systems to guide the controls of actuators, robots and smart agents. As distributed AI/robotics applications may involve a great number of |
|devices and computational resources (edge and cloud), one key challenges that affect the adoption of the technologies is the programming and deployment |
|model for the applications. |
| |
|The project will develop in-network programming approaches to enable rapidly express and deploy distributed AI systems and to enable efficient |
|information acquisition, delivery, and processing, with special focus on distributed deep learning systems and distributed reinforcement learning |
|systems, as well as develop an application deployment framework to allow application logic, application networking topologies, and traffic |
|forwarding/controlling policies to be dynamically and flexibly deployed and modified on robots, edge devices, in the network, and in the cloud to meet |
|the manufacturing production needs. |
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|DURATION OF PROJECT: Maximum 48 Months |
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|FUNDING AGENCY: Science Foundation Ireland |
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|TYPE OF DEGREE OFFERED: PhD – Full Time |
|QUALIFICATIONS REQUIRED: BSc, BEng with Honours Degree level 2.1 or Higher. English: Minimum IELTS 6.0 with no Band less than 5.5 (for students with a |
|degree from a non-English-speaking country); Strong knowledge in computer networking and/or machine learning; Good experience in C/C++, Python and Linux.|
| |
|SUPERVISORS: Dr. Brian Lee, Dr. Yuansong Qiao |
| |
|APPLICATION PROCESS: |
|The application forms are available from Susan Carroll, Office of Research, Athlone Institute of Technology, Tel: 0906483061, email: scarroll@ait.ie or |
|from the link below |
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|Completed application forms must be submitted to Susan Carroll (scarroll@ait.ie), Office of Research, Athlone Institute of Technology, Dublin Road, |
|Athlone, Co. Westmeath, Ireland |
| |
|Closing date for receipt of completed application forms is 5pm 25th March 2018 |
| |
|INFORMATION ENQUIRIES TO: |
|Name: |Dr. Brian Lee , Dr. Yuansong Qiao |
|Email address: |blee@ait.ie, ysqiao@research.ait.ie |
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