At the University of Antwerp (Belgium), there is a vacant
position for a pre-doctoral researcher at the Department of Mathematics,
Statistics and Actuarial Sciences 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 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 four-year
position (with annual evaluation), a net monthly grant of about 1500 euro, and
a stimulating working environment in a lively cosmopolitan city.
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.