Master in Atomistic and Multiscale Computational Modelling in Physics, Chemistry and Biochemistry

Specialization: Atomistic and Multiscale Computational Modelling in Physics, Chemistry and Biochemistry

• Advanced Computer Tools
• Advanced Methods for Molecular Simulation
• Applied Mathematical Methods
• Complex Networks
• Computational Biochemistry
• Computational Systems Biology
• Computer Tools
• Condensed Matter
• Electronic Structure in Solids
• Electronic Structure
• Final Project
• Fundamental Principles of Statistical Mechanics
• Introduction to Scientific Computing
• Modeling of Nanomaterials and Surfaces
• Molecular Modelling
• Molecular Structure and Chemical Reactivity
• Multiscale Modelling
• Multiscale, Coarse-Grained Methods, and Mixed Methods
• Quantum Dynamics
• Soft Matter

The main objective of the interuniversity master's degree in Atomistic and Multi-Scale Computational Modelling in Physics, Chemistry, and Biochemistry is to provide the tools to model processes of chemical, physical, or biochemical interest at various sizes or time scales, from the atomic scale to the mesoscale. To achieve this goal, students will acquire the knowledge in quantum and statistical mechanics necessary to understand the different families of methods and approaches available according to the spatial and temporal scale. Also, during the practical sessions of these studies, students will become familiar with the practical application of these techniques (using standard computer packages or developing specific applications) and with the computer and programming tools necessary to develop them.

Another objective of this master's degree is to provide the necessary training to be able to work in R&D&I research centers, both in the public and private sectors. The practical training offered in this master's degree in different fields of computation, programming, and data processing constitutes a set of very versatile, general, and practical knowledge of interest for many areas of technological development, such as the analysis and modeling of big data, technological management, consulting, and audit, or the development of computer applications, among others.

Competences

• Skills to deliver scientific presentations orally and in written form in the three languages used in the master's degree.
• Capacity to consult and understand information from scientific literature and databases, and to analyze scientific and technical documents in English.
• Ability to work in a coordinated manner in the preparation and development of a project.
• Capacity to apply the acquired knowledge to problem-solving in new or relatively unknown environments.
• Capacity for analysis, synthesis, global perspectives, and the application of knowledge to practical cases.
• Ability to work in IT environments associated with the supercomputing employed in applications for atomistic and multiscale modeling.
• Capacity to write in high-level programming languages and understand the basic concepts of parallelization and optimization of programs.
• Capacity to write scripts to perform complex tasks involving different programs and operating system commands.
• Understanding of the mathematical bases of the most common modeling methods and their computational numerical implementation.
• Understanding of the different length and time scales in nature and the physico-mathematical formalism applied in each of them.
• Understanding of the physical laws that govern the behavior of physicochemical systems relevant to balance (solids, fluids, solutions, surfaces, interfaces, macromolecules, colloids, biopolymers, nanoparticles, etc.) in conditions of balance.
• Understanding of the physical laws that govern the behavior of systems out of balance (relaxation processes, transport phenomena, chemical reactivity, reaction-diffusion processes, phase changes in physicochemical and biochemical systems, metabolic processes, signal transduction, etc.)
• Capacity to evaluate and select the length and time scales in which a phenomenon occurs, given a material, physical, or chemical phenomenon, or complex system to be modeled.
• Capacity to evaluate and select the best simulation and modeling techniques to describe a phenomenon in terms of its spatial and temporal scale, given a particular material, physical or chemical phenomenon, or complex system to be modeled.
• Understanding of the limits of computational implementation for each methodology studied, and the ability to discern the most appropriate approach for each real case study.
• Capacity to use different software packages to study the electronic structure of molecules and solids, as well as their transport properties and chemical reactivity.
• Capacity to use different software packages to study the structure and properties of solids, fluids, solutions, macromolecules, biopolymers, surfaces, nanoparticles, interfaces, and colloids.
• Capacity to use the different software packages available that allow the application of different standard molecular modeling techniques.
• Understanding of the concepts behind simulation techniques based on force fields and multiscale simulation techniques based on coarse-graining models.

Students who attend and complete this master's degree will be prepared to work in fundamental or applied advanced research, both in public and private R&D&I centers. An important outcome for the students who complete this master's degree and who are interested in continuing to carry out tasks of research will be the accomplishment of a doctorate in an area of research in which molecular modeling is important. In the BKC and the Barcelona hub, there are different research groups dedicated to computational modeling in different fields of Physics, Chemistry, and Biochemistry in which the students will be able to pursue a doctorate. Likewise, they would not have any problem should they continue their doctoral studies in any of the universities of the European Higher Education Area or other continents.

Besides, the applied knowledge of scientific models and programs that students will acquire, along with their advanced training in computer science and programming, will offer them the possibility to work in different environments. Some of them include R&D&I departments and business management units of the technology sector: companies that need to analyze complex control systems and networks, analysis, and modeling of big data; pharmaceutical companies; companies dedicated to the environment or energy technologies and materials; companies in technology consulting and audit, software development companies, etc.