Martí i Franquès MSCA-COFUND-DP. Call for 1 PhD position in "Particulate models for fluid...

The Martí i Franquès COFUND Doctoral 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.

The positions are based on individual projects encompassing all areas of research at URV: Sciences, Health Sciences, Arts and Humanities, Engineering, Social and Legal Sciences. Prospective candidates can find here the full list of projects . The application process is entirely electronic.

Through MFP, URV is in a unique position to offer the best conditions for doctoral training, based on the principles of the European Charter for Researchers  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 EU Principles for Innovative Doctorate Training .

Description of the research project (ref. 2021MFP-COFUND-8 )

Mesoscopic heat transport is of vital importance in miniaturised systems, such as molecular motors, microelectronic devices, but also in reactive fronts and interfaces. Large temperature gradients may induce strong couplings between non-equilibrium processes which are of paramount importance in the understanding and modelling of energy transfer at the nano-scale.

Simulation methods, such as Dissipative Particle Dynamics with energy conservation (DPDE), are suitable for the analysis of heat flow at the microscale, as they can describe the effect of thermal fluctuations in the field dynamics. DPDE was introduced by the URV team, and has been recently extensively applied. At present, a generalised DPDE model (GenDPDE) can describe microscopically complex systems, in which not only heat but changes in local compositions may occur, in parallel with chemical reactions. The main objective of this thesis is to contribute to the ongoing development of the GenDPDE, notably through the study of the transport properties of the model (viscosity, thermal conductivity, diffusion coefficients, etc.) as functions of the model parameters of GenDPDE. The outcomes of this research will allow us to map the model parameters to simulate real complex systems under non-equilibrium situations.

Highly desirable attributes of the ideal candidate:

• Demonstrated previous experience in one or more of the following topics: programming in scientific languages is a necessary condition (see below). A strong background is required in the Physics of Fluids and Statistical Mechanics.
• Hold a Master degree, or equivalent, in: Physics, Applied Mathematics, Mechanical, Chemical or Aeronautical Engineering, or Physical Chemistry.
• Language skills: The successful candidate must be fluent in English.
• Specific Software skills: the preferred scientific languages are Matlab and Fortran, followed by C, C++ or Python.
• Personality traits: the successful candidate must be capable of teamwork, show initiative and creativity, and comply with the ethical guidelines of the university.

References