The Department of Computer Science of the University of Pisa is happy to announce the opening of a fully funded post-doc position within the H2020 "plan4res" project
The position is formally for one year, but funds are available for it being renewed for a second year subject only to mutual interest. Further extensions after the end of the project are also possible, still subject to mutual interest. The salary will be of 30000 Euro per year, subject only to Italian personal income taxes; this is roughly 150% of the typical salary of a position of this kind in Italy.
The procedures to apply are described at
https://www.unipi.it/ateneo/bandi/assegni/asse2018/inf/30lug2018/index.htm
with deadline for application on 30/07/2018 at 13:00. Candidates on the short list will be interviewed on 07/09/2018 at the Department of Computer Science of the University of Pisa; however, remote interviews are possible. The start of the position is expected to be 01/10/2018.
The position will be entirely devoted to the development of SMS++, an innovative C++ framework for representing and solving large-scale optimization problems with multiple, nested, heterogeneous forms of structure, in particular (but not exclusively) by mens of decomposition approaches, both in sequential and in parallel. A description of the framework and of some of its possible applications is available at
https://www.plan4res.eu/wp-content/uploads/2018/06/slides.pdf
https://www.plan4res.eu/wp-content/uploads/2018/06/slides-1.pdf
The main application foreseen in the project is to long-term energy optimization problems with quite accurate depiction of the mid-term (reservoir management) and short-term (unit commitment) aspects.
Consequently, candidates are especially welcome who have:
- experience in object-oriented programming, especially in C++, for the development of complex software frameworks, in particular (but not exclusively) for the development of numerical optimization algorithms;
- familiarity with techniques for development of parallel software;
- familiarity with the main optimization techniques for large-scale structured optimization problems, in particular (but not exclusively) decomposition methods.
For further information, do not hesitate to contact Antonio Frangioni <frangio@unipi.it>. Thank you in advance for circulating this announcement to all who may be potentially interested.
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