Where: University of Pisa, Italy
When: application deadline June 19th, 2024
Title: Models and methods for energy optimization in the presence of energy aspects
Description:
In the context of the PRIN2022 project “Large-scale optimization for sustainable and resilient energy systems” (2022BMBW2A), the Department of Computer Science of the University of Pisa (DI-UNIPI) is happy to announce the availability of a 1y post-doc position (“assegno di ricerca”), salary of 21888,48€/year (net of contributions but gross of personal income taxes).
The position is open to candidates with a MSc degree, STEM fields preferred, with focus on mathematical optimization. PhD may be a plus. Programming skills (especially C++) are desirable.
The project is Models and methods for energy optimization in the presence of energy aspects and the actual research line is quite open to negotiations with the winner, provided it is related to “energy” and “optimization”. The research team at DI-UNIPI has state-of-the-art know-how and facilities for modelling and solving large-scale, challenging mathematical optimization problems related to energy systems, including access to powerful computational servers.
Contributions to the open-source C++ framework SMS++ in its energy-related modules, general-purpose modules, or both will be highly appreciated. All sorts of energy optimization problems can be considered, starting from any variant (deterministic or stochastic) of Unit Commitment, Optimal Power Flow, Optimal Transmission Switching, mid-term energy reservoir optimization, long-term energy system design, Energy Community design and operations, and basically any other. Interesting algorithmic techniques include, e.g., decomposition methods (Lagrangian Relaxation, Column Generation, Benders’ Decomposition in any possible combination), Branch-and-Bound, large-scale math-heuristics, and any contribution to subproblems of interest in these approaches.
The Postdoc will be included in a vibrant research environment, with the possibility to collaborate with other active research projects such as RESILIENT.
The position is fully funded for one year, extensions can be evaluated subject to mutual interest.
Details, requirements and instructions to apply (must read): https://bandi.unipi.it/public/Bandi/Detail/1c421117-e350-4922-8917-d17752a3a180
Pure online application at: https://pica.cineca.it/unipi/ass-inf2024-9/
Contact: Antonio Frangioni frangio@di.unipi.it