Machine Learning Based Mathematical Models for Energy Prediction - 2026_IDR_DEIB_20

Position: Research appointment (pre-doc) Institute: Polytechnic of Milano
Posted on: 26/03/2026 Deadline: 30/04/2026

Scientific-Disciplinary Group

09/IINF-05 - Information Processing Systems

Description

The goal of the research programme is the design of mathematical models based on machine learning tools for energy problems related to prediction. The application domains include both industry and climate changes. The first two months will be devoted to the study of the mathematical models necessary for the development of the project. The following two months will be devoted to the study of the theoretical properties of these models. From the fifth month to the eighth month, the most promising prediction algorithms will be experimentally compared. In the last four months, tests will be carried out to evaluate the performance of the solution produced and a prototype.

Job posting website

https://www.polimi.it/en/bandi-incarichidiricerca

Number of positions

1

Funding body

Politecnico di Milano

How to apply

https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079

Selection process

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In order to participate in the selection, please read the call ("bando") available at the following website: https://www.polimi.it/en/bandi-incarichidiricerca Oral test aimed at ascertaining candidates’ aptitude and suitability to carry out the research activity covered by the Fellowship, as well as at assessing their knowledge of English and/or other languages relevant to the research activities to be performed (up to 40 points) Relevance and pertinence of the publications, theses and scientific products attached to the research programme covered by the Fellowship (up to 10 points) Relevance and pertinence of previous research activities and work experience, if any, in relation to the research activity covered by the Fellowship (up to 30 points) Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 20 points)

View the original posting on the MUR website: Go to MUR website

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