Duration: 3 years

Scientific disciplines: Chemistry – Geosciences – Environment

Submission: The application will be published on the PhD programme website: https://www.dindistegeo.it/. We invite interested candidates to follow the updates online.

About

The University of Bari Aldo Moro (Italian: Università degli Studi di Bari Aldo Moro), founded in 1925 in Bari (Apulia region), in Southern Italy, is a prestigious Italian higher institution. With a student population of around 60,000, the University is one of the Italian higher institutions ranked in the top 2.1% by the Centre for World University Rankings (CWUR) (https://www.uniba.it/en).

The Department of Earth and Geoenvironmental Sciences, part of the University for over 90 years, carries on this rich and ancient legacy to provide a coherent reference for students interested in transdisciplinary earth sciences (http://www.geo.uniba.it/).

TIMAC AGRO Italia S.p.A. is the Italian subsidiary of the French group Roullier, a world leader in crop, animal, and human nutrition with over 10,000 employees on five continents, and a Research and Innovation Centre, the Roullier World Innovation Centre (CMI), the largest private research centre in Europe dedicated to crop nutrition, that generates yearly tens of cutting-edge technologies (https://it.timacagro.com/).

Project: In collaboration with TIMAC AGRO Italia S.p.A. and with the co-funding of the Italian National Recovery and Resilience Plan (NRRP) – Next Generation EU (NGEU), the Department of Earth and Geoenvironmental Sciences is advertising a full industrial PhD grant for a three-year period to “Development of strategies for nutrient recovery from waste streams for contributing to the fertiliser industry’s sustainability”. The grant foresees a period between 6 and 12 months in a prestigious international institution relevant to the study field.

Eligibility: We seek an active and motivated student who has successfully completed an MSc or MEng in Geological sciences or Chemistry or Environment (or related fields), has strong academic records from a recognised institution, and is interested in modelling. Other eligibility criteria are:

• Proficiency in English, the research language;

• Competence in new modelling techniques (machine learning and AI frameworks, data sciences, etc.)

• Recommendation letters from academic or professional referees;

• A motivation letter to explain the driver to participate;

• An updated CV;

• Previous research experience or work experience in the relevant field can be an advantage.

For more information, contact Prof. Daniela Pinto (daniela.pinto@uniba.it) or Dr Daniel El Chami (Daniel.elchami@roullier.com).