[DMANET] Joint Ph.D. Position: LIX - Ecole Polytechnique and Dipartimento di Informatica - Università di Pisa

We are pleased to announce the availability of a fully-funded, three-year Ph.D. bourse funded by the PGMO Project "Consistent Dual Signals and Optimal Primal Solutions"

http://www.di.unipi.it/di/groups/optimize/Projects/PGMO/

The successful candidate will spend three years between LIX - Ecole Polytechnique (Saclay, Paris, France) and Dipartimento di Informatica - Università di Pisa (Pisa, Italy) to work on complex, real-world energy optimization problems. The salary will be 33,333EUR/year gross for a non-renewable maximum of three years, which should roughly correspond to 1500-1600EUR/net plus social security (the precise amount depends on the personal situation and cannot be foreseen precisely). A substantial part of the work will entail close collaboration with Électricité de France (in particular the Osiris research group) under the auspices of the Gaspard Monge program for Optimization and Operations Research

http://www.fondation-hadamard.fr/fr/PGMO

The expected research line will mainly focus on the interplay between advanced decomposition approaches (inexact, disaggregated, generalized bundle methods ...) and Mixed-Integer (Non)Linear optimization techniques (branch&something, cutting planes/surfaces, reformulations, ...) for the solution of very-large-scale, structured, difficult optimization problems, possibly taking into account uncertainty in the data (such as that related to renewables production). The candidate will be jointly supervised by Antonio Frangioni (Dipartimento di Informatica - Università di Pisa), Claudia D'Ambrosio and Leo Liberti (LIX - Ecole Polytechnique); a jointly-issued or doubly-issed Ph.D. degree between the two Doctorate Schools is expected. Collaboration with other prominent researchers of the field is also expected.

Candidates willing to apply for the position are required to send a CV and a motivation letter to Antonio Frangioni (frangio@di.unipi.it); recommendation letters are welcome but not mandatory. The selection is expected to take place in September, with the position remaining open until fullfilled. The ideal candidate should be interested in all aspects of the development of complex optimization models and solution techniques: (re)formulation, theoretical analysis, implementation, computational testing, verification of the real-world impact of the obtained solutions. Knowledge of basic mathematical optimization methods and reasonable implementation skills (C++ programming, experience with optimization solvers) are expected, although of course each part can and will be honed during the term.
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