Statistical methods for large, complex and structured data

Italian Ministry of Education, University and Research; Italia; In loco; EUR 40.000 - 60.000; Tempo pieno

Descrizione del lavoro

Scuola Superiore Sant'Anna di Pisa invites applications for a Researcher position in economics, focusing on developing novel statistical methodology for inference in high-dimensional data and complex problems. The project is within the EMbeDS Department of Excellence and emphasizes sparse, interpretable learning, feature selection, and clustering, with strong cross-disciplinary collaboration.

The position seeks researchers with a strong background in statistics and econometrics, willing to

Descrizione del lavoro

Organisation/Company Scuola Superiore Sant'Anna di Pisa Research Field Economics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 9 Oct 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 will focus on the development of novel statistical methodology for inference in large, complex and structured problems – such as those arising from high and ultra-high dimensional data; graph and network-valued data; functional data; multi-modal data; etc. A particular emphasis will be placed on sparse and interpretable statistical learning methodology; scalable techniques for feature selection, dimension reduction and assumption-free testing; computational assessments of significance and stability; and approaches for latent structure recovery and clustering. The research will take place within the interdisciplinary environment supported by the L’EMbeDS Department of Excellence (Economics, Management and Law in the era of Data Science), drawing upon statistical theory and computational tools to foster multiple collaborative endeavors and translate methodological innovation into impactful domain applications.

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Eligibility of fellows: country/ies of residence:

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Eligibility of fellows: nationality/ies: