Norway - SINTEF ICT Postdoc Position in Parallel Methods for Transportation Optimization

SINTEF ICT is an institute within the SINTEF Group. SINTEF ICT undertakes research and development projects for industry, the public sector, and funding agencies in the area of information and communication technology. SINTEF ICT has approximately 280 employees and collaborates with a large number of industries and academic institutions in Norway and abroad. The Department of Applied Mathematics at SINTEF ICT performs research activities within modeling and simulation of petroleum reservoirs, geometric modeling, visualization, parallel and heterogeneous scientific computing, and optimization methods for complex planning and scheduling applications.

SINTEF ICT offers a temporary research position in parallel and collaborative methods for transportation optimization in the period July 1 2009 until December 31 2011.

The Project
The Department of Applied Mathematics has recently acquired a research project in parallel and collaborative methods in transportation optimization (Collab), with focus on rich vehicle routing problems and the dynamic shortest path problem. We are currently seeking an innovative postdoctoral researcher with excellent skills in mathematics, operations research, and parallel computing.

The postdoctoral researcher will be a key resource in Collab. The project team consists of highly competent colleagues from the Group of Optimization and the Group of Heterogeneous Computing at SINTEF ICT, as well as top level researchers from the associated research partners:

• AIL, University of Jyväskylä, Finland (principal researcher: professor Olli Bräysy)
• CIRRELT, Canada (principal researcher: professor Michel Gendreau)
• ITMMA, University of Antwerp, Belgium (principal researcher: professor Wout Dullaert)

Qualifications

• Doctoral degree in applied mathematics, discrete optimization, operations research, transportation optimization, parallel computing, or related subjects
• Solid background in mathematics and parallel computing
• Good knowledge of exact and metaheuristic methods for transportation optimization
• Strong publication record
• Experience with software implementation
• Good social skills and the ability to work independently as well as in a team
• High ambitions and strong focus on the project goals

Experience with development of parallel and collaborative methods in transportation optimization is an advantage, but not a strict requirement.