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

| |

|OVERVIEW: |

| |

|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. |

| |

|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. |

| |

|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. |

| |

|DURATION OF PROJECT: Maximum 48 Months |

| |

|FUNDING AGENCY: Science Foundation Ireland |

| |

|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 |

| |

| |

|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 |

[pic]

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download