• Organization
  • Coordinator
  • Secretary
  • Advisory Commettee
  • Delegate for Foreign Students
  • Commission for Education
  • Quality Assurance Group (Gruppo Riesame)
  • Guideline for PhD courses
  • Minutes
  • Documents
• People
  • PhD Student - XLI cycle
  • PhD Student - XL cycle
  • PhD Student - XXXIX cycle
  • PhD Student - XXXVIII cycle
  • PhD Student - XXXVII cycle
  • Ph Doctors
  • Faculty - XLI cycle
  • Faculty - XL cycle
  • Faculty - XXXIX cycle
  • Faculty - XXXVIII cycle
  • Faculty - XXXVII cycle
  • Faculty - XXXVI cycle
  • Faculty - XXXV cycle
  • Faculty - XXXIV cycle
  • Faculty - XXXIII cycle
  • Faculty - XXXII cycle
  • Faculty - XXXI cycle
  • Faculty - XXX cycle
• Admission
• Education
  • CFU Guidelines
  • Courses
    • Courses - XLI cycle
    • Courses - XL cycle
    • Courses - XXXIX cycle
    • Courses - XXXVIII cycle
    • Courses - XXXVII cycle
    • Courses - XXXVI cycle
    • Courses - XXXV cycle
    • Courses - XXXIV cycle
    • 2019
    • 2018
    • 2017
    • 2016
    • 2015
    • 2014
  • Courses Calendar
  • Evaluation_procedure
  • Seminars
• Research
  • PhD Thesis Proposals
  • Students & Teachers Awards
• Collaborations
• Employment
• Contacts
  • How to Reach us
• International

Welcome to the website of the PhD Course in "Models and Methods for Material and Environmental Sciences"

The Course aims at the training of experts in advanced research methodologies in environmental and material sciences.The research doctor will be able to operate in one or more of the following fields: processes regulating the transfer of elements and compounds from geosphere to hydro- and biosphere; forecasting, prevention and mitigation of natural risks; identification and optimal use of resources; study, conservation and appraisal of cultural assets; biodiversity assessment; environmental impact of human activities; chemical sustainable strategies; preparation and characterization of materials with innovative functional properties; devices and methodologies for electrochemical sensing suitable to work in real systems; computational multiscale strategies; chemometrics, multivariate analysis of signals and images.

Highlights