Ph.D. position @ University of Antwerp
At the University of Antwerp (Belgium), there is a vacant position for a
pre-doctoral researcher at the Department of Environment, Technology and
Technology Management in the Faculty of Applied Economics. The ideal
candidate has a good background in statistics and mathematics, including
good programming skills and a good command of the English language.
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 Sorensen.
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 1600 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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