[Opt-net] Two-years Post-Doc position in structured MINLP

[Antonio Frangioni]

The Operations Research Group of the Department of Computer Science of the University of Pisa will welcome applications for a fully-funded, two-year Post-Doc position. The field of interest will be the development of innovative approaches to structured Mixed-Integer (Linear and) NonLinear Programs and their application to real-world problems, usually with a strong graph-network structure, in areas such as telecommunications (e.g. routing and design problems in power- and latency-constrained networks) and transportation/logistics (e.g. scheduling and routing problems in home care applications). The ideal candidate should combine previous expertise, or at least keen interest, in the above-mentioned topics (MILP and MINLP techniques, convex optimization) with a taste for experimental work; experience with MINLP modeling/solution tools and with best practice in optimization software development will be a definite plus.

The position will be formally announced at

http://www.unipi.it/ateneo/bandi/assegni/2012/info/index.htm

in the next few days. The selection process will (necessarily, by law) comprise a meeting for discussion with the candidates; however, it will be possible (and strongly encouraged) that the latter is accomplished by any form of remote communication means (skype, ...). The candidates are therefore encouraged to contact

Antonio Frangioni (frangio at di.unipi.it)
Maria Grazia Scutella' (scut at di.unipi.it)

after submission to arrange for these technical details; requests for clarifications about the position and/or help in the submission process are also welcome. The selection process is expected to be finished by the end of April, with the position starting shortly thereafer; some (but not much) wiggle room could be possible with the dates if strictly required. The salary for the position will be 23000 Euro per annum gross (about 18000 net), and the position will have the legal status according to the applicable Italian laws and regulations.