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PhD Project in Computer Science / Computational Intelligence, Swinburne University of Technology, Melbourne [Australia]

PhD Project in Computer Science/Computational Intelligence (Fitness/Search Space Characterisation with a View to Choosing Problem Solvers and their Parameter Settings)@Swinburne University of Technology (Melbourne, Australia)

Project title:
Fitness Space Characterisation for Stochastic Combinatorial Optimisation

Research topic:
Stochastic optimisation methods such as Genetic Algorithms and other evolutionary approaches are used to find approximate solutions to combinatorial problems when the problems are too complex to be solved deterministically through mathematical approaches.

So far, evolutionary algorithms have been applied to individual combinatorial problems such as bin packing and resource allocation. Certain algorithm and parameter variations are regularly reported to improve results obtained from a particular problem. This project aims at investigating ways – stochastic, mathematical or statistical – of probing the fitness space for clues about the characteristics of the problem’s fitness space.

The ultimate goal is to find common characteristics of problems and to identify the solvers, which work best for such characteristics.

Your Benefits:
- The topic is broadly based. You can apply your own ideas as well as approaches you are comfortable with.

- You will be trained in all skills that are required to successfully finish your research project. Our goal is to help you develop the skills, connections, and opportunities required to commence a successful academic career.

- You will be given advice on how to publish high-quality research as well as where to publish it. At least one major publication in a highly ranked international conference or journal is expected.

- You will work mostly independently, but you will receive timely feedback and advice on your work and progress.

- You will study in a friendly and cooperative environment. Australia has high living standards and a welcoming atmosphere.

We require
a PhD student who has a good academic record (first class honours or equivalent with marks above 80-85%) with background in one or more of the following areas:

  • Application of stochastic solvers such as Genetic Algorithms
  • Knowledge of basic statistics and mathematics, advanced concepts are an advantage
  • Programming skills in one contemporary programming language
  • Ability to design and structure reliable software programs.

Personal attributes such as performance, dependability, availability, motivation and honesty are of equal, if not greater, importance.

Communication and writing skills are an advantage to all researchers. Writing classes are, however, available to PhD students.

The scholarship carries a value of AUS$22,500+ p.a. and a tuition fee waiver. The selection process will be competitive. If you are interested in the research project, please provide the following information via email to: imoser[ at ]swin.edu.au:

  • detailed curriculum vitae
  • an (electronic) copy of undergraduate and postgraduate transcripts (first class honours or equivalent with marks above 80-85% or GPA 3.70/4)
  • evidence of English proficiency for non native English speaker (minimum requirement of IELTS 6.5 with no band below 6.0, scores above 7.0 are preferred).
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