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 renewable 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 ([log in to unmask]);
recommendation letters are welcome but not mandatory. The selection is
expected to take place in September, with the position remaining open
until fulfilled. 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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