Scientific machine learning for the numerical simulation of complex systems - 2026_IDR_DMAT_2

Organisation/Company Politecnico di Milano Research Field Mathematics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 31 Mar 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 research project focuses on the analysis and implementation of scientific machine learning techniques for building efficient reduced-order models in the context of the numerical simulation of parameterized partial differential equations. The analysis of recent deep learning paradigms (such as self-attention mechanisms) in the context of reduced-order models, as well as their application to areas of interest in engineering like, e.g., computational fluid dynamics, are key activities of this research program. FIS Starting Grant "DREAM" (FIS00003154), CUP: D53C23003180001

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 20 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 20 points)

Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 20 points)

EUROPE

Eligibility of fellows: country/ies of residence:

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