- Presentation
- Training activities
- What do we research on?
- Research lines
- PhD supervisors
- Admission and enrolment
- Assessment
- Financial aid and tuition fees
- Quality and indicators
- DOCTORAL THESES
- Programme coordination
| Dr. Alex Fragoso | alex.fragoso(ELIMINAR)@urv.cat |
- Programme Academic Committee
| Dr. Alex Fragoso (president) | Dr. Jordi Riu Rusell (secretary) | |
| Dr. Francisco Medina Cabello | Dr. M. Carme Güell Saperas | |
| Dr. Marta Giamberini | Dr. Carlos Pozo Fernández | |
| Dr. Dieter-Thomas Boer | Dr. Jordi Pallarès Curto | |
| Dr. Magdalena Aguiló Diaz |
- Offer
| Places available | 50 |
- Language
- English
- Introduction and objectives
This programme aims to provide future professionals with a strong sense of innovation in specialised fields of Nanotechnology, Materials and Chemical Engineering that are especially oriented towards carrying out research in public institutions and industry.
The programme aims to build and strengthen research capacities through advanced practice in a research project that allows the students to prepare and defend a doctoral thesis based on original research.
During the period of preparation of the doctoral thesis, the programme will develop the generic competencies that are necessary for a successful career in any of the above areas.
- An inter-university doctorate
The doctoral programme in Nanoscience, Materials and Chemical Engineering is organised and coordinated by the URV in collaboration with the following institutes and educational establishments:
Participating institutes and establishments
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- Career opportunities
The doctoral degree allows students to obtain the knowledge and skills needed to work in the following areas:
- Industry.
- Research and development.
- Auxiliary teaching and services in industry related to experimentation and logistic design involving new nanostructured and catalytic materials, devices, nanomedicine, biomedicine, cosmetics, biomaterials, water treatment and purification, membrane technology, etc.
- Polymer design and computational data analysis and modelling.