The Martí i Franquès COFUND Doctoral Fellowships Programme (MFP) is a redesign of the existing MF programme, offering 100 doctoral contracts (in four editions : 2017, 2018 and 2020, 2021) at the Universitat Rovira i Virgili (URV).
The programme is uniquely shaped to offer the best training stemming from the "triple i" principles of the Marie Sklodowska-Curie Actions : international, interdisciplinary and intersectoral.
In order to achieve these goals, we combine leading research groups at URV with scientific partners from world-class institutions, such that the candidates are be exposed to interdisciplinary training as well as mentoring from the industrial sector.
Through MFP, URV is in a unique position to offer the best conditions for doctoral training, based on the principles of the and the Code of Conduct for the Recruitment of Researchers (guaranteed by the HR award that URV has received in 2014), as well as the .
This position is reserved exclusively for candidates with disabilities. ONLY they can participate, and all candidates that cannot prove their disability via an official certificate will be rejected.
Description of the research project (reference : 2020MFP-COFUND-22)
Project motivation & description : The need to transition towards a more sustainable industry calls for advanced multi-objective decision-support tools embracing the three sustainability dimensions economic, environmental and social).
In this PhD project, we will develop process systems engineering concepts and tools to assist in the design and planning of more sustainable chemical processes, with emphasis on reducing water and energy consumption as well as waste and emissions in the production of a wide range of chemicals.
this approach will be applied to major conventional chemical processes and emerging alternatives, including carbon capture and utilization, biomass & waste conversion, and polymers revalorization.
The PhD project will, therefore, advance a more fundamental understanding of how to embed sustainability principles in the chemical industry, while developing tailored computational tools to assess and optimize a wide range of interconnected chemical routes.
life cycle assessment and related software packages SimaPro, Ecoinvent); algebraic modelling systems GAMS, Matlab), optimization solvers CPLEX, DICOPT, SBB) and machine learning algorithms artificial neural networks, support vector machine, etc.
The PhD project is embedded into a larger, interdisciplinary research effort with international collaborations.
Required Research Experiences