The position is meant to conduct research on the algorithmic construction of optimal designs of experiments. The work, which involves the implementation of operational research ideas in optimal experimental design, will be carried out in close collaboration with Peter Goos and Kenneth Sörensen. The candidate is expected to enroll the university's Ph.D. program and to obtain a Ph.D. at the end of the project. A short project description can be found below.
We offer a three-and-a- half to four-year position (with annual evaluation), a net monthly grant of about 1700 euro, and a stimulating working environment in a lively cosmopolitan city.
For more information, please contact peter.goos@ua. ac.be
Short project description:
Innovation and quality improvement are crucial for businesses and industries in today's world of global competition: only innovative, top-quality products and process technology can provide companies with a strategic competitive advantage and guarantee a leading technological position. The purpose of this project is to develop a framework for supporting product and process innovation through designed experimentation that guarantees a reduced time-to-market, enhanced customer satisfaction, increased market share and acceptably low cost of production. The framework will also be useful for the improvement of existing products, processes and services.
Many sorts of businesses experience similar problems in the early stages of a product's or process's life cycle. Sooner or later, they are confronted with the need to investigate the impact of several parameters on products, processes and consumers. More often than not, their studies must be carried out under an enormous time pressure so as to keep the time-to-market limited and maintain or acquire first-mover advantages if possible. This calls for a coherent generic scientifically- sound time-and cost-efficient approach to product and process innovation.
Optimal design of experiments is such an approach. However, the construction of optimal experimental designs involves solving complex combinatorial optimization problems. This interdisciplinary research project is intended to implement state-of-the- art methodology for single- and multi-objective optimization from operational research (where, for instance, vehicle routing problems, assignment problems and project planning problems are studied) in optimal design of experiments.
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