CISR PhD and Postdoctoral Positions
Simulation and Scheduling Appointments
The Centre for Intelligent Systems Research is offering a three year postdoctoral appointment and a PhD scholarship for an industry-based research project with Boeing and General Motors - Holden. The project will suit outstanding individuals interested in furthering their careers in the area of intelligent systems.
This research will develop methods to optimise and schedule networks of smart and traditional cameras in a manufacturing environment, to enable knowledge capture, manage performance and identify causes of quality degradation. Excellent software development and effective communication skills are essential.
The PhD scholarship is for a three year fixed term, with a stipend of $28,715 per annum available to the successful applicant. The award is open to domestic and international students.
Interested applicants should apply online at http://www.deakin.edu.au/future-students/research/how-to-apply.php or contact Professor Nahavandi saeid.nahavandi@deakin.edu.au for further details.
Applications close 6th June 2012.
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The Centre for Intelligent Systems Research is continuously looking for high quality students and postdoctoral fellows interested in furthering their careers in the area of intelligent systems. CISR currently has opportunities for PhD's and postdoctoral fellows in modelling and simulation, scheduling, manufacturing, robotics, human performance and haptics.
For further information please forward a copy of your CV and academic transcript to Professor Saeid Nahavandi
or Dr Douglas Creighton.
Enabling ambient intelligence for manufacturing processes through distributed camera networks
This project will develop methods to optimise and schedule networks of smart and traditional cameras in a manufacturing environment, enabling knowledge capture, manage performance and identify causes of quality degradation. This research will assist Australian manufacturers to stay competitive in the dynamic global market.
Regional Science and Technological Innovation through Information Analysis and Optimisation of Systems and Technology
Deakin University and the University of Ballarat will complete joint research projects, as part of a Collaborative Research Network, studying the optimisation of systems and processes to revitalise regional industry, manufacturing, health systems and related service delivery.
Research Projects:
- Metamodelling and Optimisation of Complex Systems
Deakin University's event simulation-based meta-modelling capability, coupled with Ballarat University's optimisation knowhow will address systems optimisation and simulation challenges to provide solutions to regional decision-makers. The research challenge is in accurate estimation, time series prediction and the integration of effective optimisation methods. Such problems in most real world applications are large scale and they may involve nonsmooth nonconvex functions.
- FEA Optimisation and Visualisation
The study of constitutive laws and physical behaviours of advanced materials, from organs and skin to nano surfaces, needs to consider non-smoothness and multi-scale effects. Modelling, design, and simulation of these advanced materials must deal with nonconvexity and large-scale deformation, which produce fundamental challenging problems in both theoretical analysis and scientific computations. This investigation will be coupled with advanced visualisation for effective communication and analysis.
- Decision support using optimisation, machine learning and constraint programming for supply chain management
Regional industries faces challenging supply chain problems, from the minimisation of inventory costs, to demand forecasting and adjustment, matching sales to capacity, production planning, and not least transport planning and scheduling and environmental impact. The research challenges in optimising regional supply chains include modelling, reinforcement learning, continuous and discrete optimisation and the integration of optimisation methods for the different sub-problems.
Artificial Intelligence in the areas of Modelling, Simulation, and Optimisation
The aim of this research program is to investigate applicability of and exploit advanced Artificial Intelligence (AI) methods for uncertainty quantification. Uncertainties associated with values predicted by AI models will be quantified and measured through construction of Prediction Intervals (PIs).
Research Projects:
- Construction of PIs: developing new techniques for generation of reliable PIs using AI methods such as neural networks and fuzzy systems. In particular, advanced type-2 fuzzy logic system will be investigated due to their excellent capability in dealing with uncertainties.
- Optimisation of PIs: how to improve the quality of PIs is the research direction. The idea is to develop PIs that are more informative (narrower) and theoretically correct (a coverage probability above the confidence level). The PI quality improvement is challenging, as the optimisation problem is multi-objective (formulation and solution).
- Application of PIs: how PIs can be used in real world decision making processes is the final stage of these research projects. PIs will be used for operational planning and scheduling in a variety of fields, such as manufacturing, energy systems, transportation system, logistic networks, and so on.
Multi-Point Haptics
Haptic interfaces have paved the way for interacting with a virtual environment in a physically realistic way. They aim to provide a transparent interface which connects to the user through a stylus that is attached to a robotic arm. This arm translates the user's motions from the real world into the virtual environment and attempts to provide reactive forces to the user's hand when they have contacted a virtual object. This single-point interaction with the virtual object should resemble all the physical characteristics of a stylus contacting a real surface. The ability to extract the desired information from a virtual object is a distinct advantage of haptic technology; however the use of single point interaction devices has hampered the natural process to reveal particular object properties.
The Centre for Intelligent Systems Research has been recognized as a haptics research facility which provides enhanced hardware and software solutions to enrich current haptics technology and allows for their expansion within applications such as medical training, to improve the learning capacity and the early experience within the medical field. Military applications such as tele-operation within dangerous environments allows for the safe assessment and disarmament of sensitive and hazardous objects. Industry applications such as operator training allows for the safe education and training of employees within industry, without being prematurely exposed to dangerous work environments.
The projects within multi-point haptic research are based on developing an extension to current haptics technology, which will provide the user with the ability to grasp and manipulate objects in complex virtual environments. This requires customised hardware development to build upon current work and consequently aim towards whole hand force feedback. The ability to control the force distribution to each finger requires the development of electronics and associated control software
- Project 1: Developing modelling methodology to determine critical process parameters and material properties
- Project 2: Force Distribution Analysis
- Project 3: Haptics Modelling of Flexible Materials
- Project 4: Haptics enabled Nano-Manipulation
- Project 5: Algebraic Computing (Programming Algebra)
- Project 6: Augmented Reality Markup Language (ARML)
- Project 7: Implicit 3D Graphics Processing for Viscoelastic Haptic Rendering (Graphics and Haptics)
- Project 8: Continuous Image Algebra: From Finite Sets to POsets and Cyclic Structures (Image Processing)
Project descriptions (96 KB)
