2026-IdrDip-01-mate - Accessibility Analysis in Road Networks and Public Transports: Models and Algorithms - cod.

13 ago - Italia
Italian Ministry of Education, University and Research

Organisation/Company Università di Pavia Research Field Mathematics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 8 Sep 2026 - 12:00 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The winner will study integer and non-linear linear optimization models to support accessibility analysis of public interest services (for example, hospitals, medical facilities, and analysis centers) through the use of public
transportation (bus, metro, trains) and road networks (for private vehicle use), considering preference profiles depending on age and other social criteria. In addition to the models, optimization algorithms will be developed (for
example, math-heuristics based on column eneration methods) in the Python programming language, using
solvers such as Gurobi and HiGHS.





The public call with detailed attendance and selection rules (Art 4 and 6) can be found at: https://pica.cineca.it/unipv/tipologia/idr
The selections are open to candidates, Italian or foreigner, in possession, on the date of the deadline for submitting applications for the admission to the selection, of a master's degree or single-cycle, degree obtained no more than six years previously are eligible to participate in the selection process,preferably in Mathematics. These degrees must be relevant to the subject of the research activity.

Further specific assessable qualifications (see Art. 1 par. 1 Call for applications):
- - Master's Degree preferably in Mathematics
- - PhD preferably in Mathematics, or related field
- - Excellent Python programming skills
- - Knowledge of MILP solvers such as Gurobi and
HiGHS
- - Availability for travel to industrial partners
- - Knowledge of medical-hospital

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