Application Deadline: 7 Sep 2026 - 16:00 (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 initial step in landslide hazard assessment involves evaluating mapped phenomena and their features. However, crucial attributes, like landslide type, may be missing, hampering somewhat the knowledge about these phenomena. The project aims to develop an AI-based solution to classify landslide types primarily using geological and geomorphological data The Research Assignment is aimed at developing Artificial Intelligence (AI) models, mainly CNN and ViT, for the automatic classification of different types of landslides based on the analysis of geological, geomorphological, and geometric landslide data
Where to apply
Website: https://pica.cineca.it/unipd/
Additional Information
Eligibility criteria
Eligible destination country/ies for fellows: Italy
Eligibility of fellows: country/ies of residence: EUROPE
Eligibility of fellows: nationality/ies: EUROPE
Selection process
- for qualifications (max 20): degree, PhD, specialization diploma, certificates of attendance of post-graduate specialisation courses (obtained in Italy or abroad);
- for the scientific-professional curriculum (max 20): documented research activity carried out at public and private entities with contracts, scholarships or assignments (both in Italy and abroad) relevant to the research activity subject of the announcement;
- for scientific productivity (max 20): quantity and quality of scientific publications, including master's or single-cycle master's or doctoral theses;
- for the interview: max 40
Website for additional job details: https://www.geoscienze.unipd.it/news/termine/86
Work Location(s)
Number of offers available: 1
Company/Institute: Università degli Studi di Padova
Country: Italy
Contact
City: Padova
Website: https://www.geoscienze.unipd.it/
