The Doctorate School in Computer Science at The University of Pisa is happy to announce the opening of two fully-funded three-years Ph.D. positions (extension to a fourth year if necessary can be considered) on
High-Performance Energy Optimization for Renewable Energy Communities (code INFO05_C)
High-Performance Public Transport Optimization (code INFO06_C)
The positions arise in the context of long-standing research lines. In particular, the first is related with the Italian PNNR “Network 4 Energy Sustainable Transition – NEST”, the PRIN project “Large-scale optimization for sustainable and resilient energy systems”, and the RESILIENT CET Partnership
(among others) for the study of optimization of energy systems at all scales, from Renewable Energy Communities to the European level. The second is rather in collaboration with M.A.I.O.R. S.r.L,
an ante-litteram spin-off of the Department of Computer Science of the University of Pisa since over 30 years a leading company in Decision Support Systems for Public Transport companies and regulators, with customers in over 100 cities in Europe, North America, the Middle East, Oceania, South America, and Asia.
Both positions will strive to push the current boundaries of optimization approaches using the innovative C++ software framework SMS++
to develop sophisticated algorithms for large-scale, hard optimization problems. Significant methodological research in fields like decomposition approaches, parallel search, and others (depending on the tastes and inclinations of the students) will have to be conjoined with dedication to significant practical applications and implementation of efficient, well-designed, well-documented, well-tested open-source software
Call website: Università di Pisa: Home Dottorato di Ricerca
Call on Energy Optimization (INFO05_C): https://dottorato.unipi.it/images/stories/competition2024_2025/concorsi_c_eng/info05_c_eng.pdf
Call on Public Transport Optimization (INFO06_C): https://dottorato.unipi.it/images/stories/competition2024_2025/concorsi_c_eng/info06_c_eng.pdf
Practical guide to apply: https://dottorato.unipi.it/images/stories/competition2024_2025/documents/guide40b_eng.pdf
For more info, please contact antonio.frangioni@unipi.it