Master's degree in
Engineering Physics
Why study this master?
Master EM-Biopham


Three Prizes of 1000 EUR to encourage research carried out by Master's students in the Physics Department of the UPC

The students of the Master's Degree in Physical Engineering at the UPC: Andrea Fontanet, Albert Civit and Axel Sanz have been awarded with the three prizes of 1000 EUR offered by the Department of Physics of the UPC this academic year 2021-22 and dedicated to supporting their research work in the Department through their Master's Thesis. Congrats to all 3!
Last July 5th we had the graduation ceremony of the 2020-21 alumni of the MEF

Photo: Josep Pegueroles (director of ETSETB), Montserrat Pardàs (vice-president of UPC), Andreu Benavent (graduate), Jordi Marti (head of studies MEF), Anna Humbert (academic secretary of ETSETB).

Three Prizes of 1000 EUR to encourage research carried out by Master's students in the Physics Department of the UPC

The students of the Master's Degree in Physical Engineering at the UPC: Mateo Alonso, Jon Garí and Eva Rifà have been awarded with the three prizes of 1000 EUR offered by the Department of Physics of the UPC this academic year 2020-21 and dedicated to supporting their research work in the Department through their Master's Thesis. Congrats to all 3!

Call for grants "JAE INTRO ICMAB 2020” addresed to master students 2020/21 is open.

Period: 1 to 20 september 2020.

List of available projects:

Those interested, fill up the forms and send them to

More information at CSIC’s web:

After successfully defending his master's thesis entitled Preparation and manipulation of free-standing oxides for photovoltaic applications, directed by Prof. Mariona Coll of the Institute of Materials Science of Barcelona, Ivan Caño Prades has become the first master's graduate in Engineering Physics at the UPC. Congratulations to Ivan and his director for the work done.
Internships for university students at ALBA Syncroton: call 2020-21

Three Prizes of 1000 EUR to encourage research carried out by Master's students in the Physics Department of the UPC

The students of the Master's Degree in Physical Engineering at the UPC: Nica Gutu, Jordi Pera and Paula Pàmies have been the winners (2020) of three prizes of 1000 EUR offered by the Department of Physics of the UPC and dedicated to supporting their research work in the Department through their Master's Thesis.
Congrats to all 3.

Trento-Innsbruck Quantum Information Tour


The Master in Engineering Physics of the UPC will be the host of the new studies of the European Master “Erasmus Mundus” Biopham

Our master studies will be undertaken by students of Biopham during the second semester of their first academic course. The scheduled kick off of Biopham is the academic year 2021-22


The master's degree in Engineering Physics is oriented towards frontier engineering based on advanced education in physics. Specialist engineering fields such as nanotechnology, nanoelectronics and biomedical engineering require an ever-growing number of professionals who have extensive training in advanced physics and sound knowledge of quantum physics, complex system physics and device physics, which can be applied both at the nanoscopic scale and in large-scale facilities.

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The master's degree in Physical Engineering is associated to content with a high labor demand.

From senior researcher or technical staff, to management and management positions, going through a project, area or department, with the possibility of becoming an entrepreneur entrepreneur

Industries with a strong technology component.

Basic and applied research centres.

Frontier engineering in the field of nanotechnology.

Doctoral training in research centres and universities.


The master program comprises 23 ECTS of common subjects, 20 ECTS of elective subjects and a master thesis of 17 ECTS. Elective subjects can be chosen among different Physics and Engineering courses. To find detailed course guides, see link to: curriculum in the web of the MEP at the Telecommunications School.


Common Subjects


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Elective Subjects in Physics


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Elective Subjects in Engineering

Max 12 ECTS

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Master Thesis


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The Department of Physics will offer 3 grants of 1000€ for students who complete the Master's Thesis in research groups of the Department, therefore, the resolution will be passed after enrollment.

The Academic Committee of the Master will award scholarships according to the academic quality parameters of the candidates.


Duration and start date

60 ECTS credits, to complete in one academic year, if starting in september and in one and a half academic year, if starting in february.


Approximate fees for the master’s degree, excluding academic fees and degree certificate fee, €1,660 (€2,490 for non-EU residents).

More information about fees and payment options.


The Department of Physics will offer 3 grants of € 1000 for students who complete the Master's Thesis in research groups of the Department, therefore, the resolution will be passed after enrollment.

The Academic Committee of the Master will award scholarships according to the academic quality parameters of the candidates.

Timetable and delivery

Mornings. Face-to-face.

Language of instruction



Barcelona School of Telecommunications Engineering (ETSETB)

Contact the master coordinator or the managing team for further information or guidance.

Student Profile

Holders of a degree, or students in the last year of studies of a degree, can apply for admission to the master in Engineering Physics. An official degree certificate is necessary the day of registration, in September. Please check the general academic requirements for master's degrees at UPC-Barcelona Tech.

The master in Engineering Physics The master in Engineering Physics is mainly oriented to graduates in engineering physics and physicists willing to broaden their education in cutting edge engineering applications and advanced physics. Other graduates in engineering or applied sciences are also invited to apply.


Related Companies

The master in Engineering Physics, due to its standing has various agreements with many companies and research centers. Below you will find a non-exhaustive list of companies related to the master

Ph.D. Program

PhD studies in Computational and Applied Physics provide a high level training in the fields of Computational Physics and Applied Physics, as well as supplying an appropriate background in the general methodologies of the scientific and technical research. Our aim is that future PhDs have the capacity to lead both research and technological innovation in the fields indicated above.

Please visit the PhD in Computational and Applied Physics website


Relevant information on the present schoolyear will be posted here.

Academic Calendar

The Academic year consists in 2 semesters, for a more detailed information check the following PDF

Academic Calendar


Subjects are usually taught in the afternoons, for a more detailed information check the following link

Master Degree Timetables

Master Degree Theses

The MEF Master Theses are governed by the following regulations

Theses regulations

Academic coordination:

Prof. Jordi Marti Rabassa

Contact phone/email:

93 401 6750

Course guide


  1. Critical phenomena
    • Mean Field
    • Scaling and renormalization group
    • Kinetic Ising models
    • Continuum models
    • Growth Models
    • Percolation
  2. Dynamical Systems
    • Flows and maps
    • Normal Forms
    • Stability; Bifurcations
    • Intermittency; Chaos
    • Pattern formation
  3. Stochastic Processes
    • Markov processes
    • Master equations
    • Stochastic differential equations
    • Fokker-Planck equations
    • Relaxation and First-passage times
  4. Introduction to complex networks
    • Small-world networks
    • Scale-free networks
    • Characterization of networks
Course guide


  1. Approximate methods in Quantum Mechanics.
    • Description of the problem. Mathematical formulation.
    • Solution of the problem using variational methods. Time-independent perturbation theory approach.
  2. Introduction to Scattering theory in Quantum Mechanics.
    • Formulation of the problem, differential cross section and Lipmann-Schwinger equation. T-matrix, Born approximation and partial wave expansions. Low-energy scattering.
  3. The many-body problem in Quantum Mechanics.
    • Bose and Fermi statistics, wave functions and simmetries.
    • Second quantization: creation and anihilation operators. Operators and observables in second quantization.
    • Hartree-Fock approximation, Gross-Pitaevskii equation and the Bogoliubov approximation.
  4. Magnetic systems
    • Polarized and unpolarized free Systems.
    • Ferromagnetic states. Single-particle excitations and particle-hole pairs. Magnons. Superconductivity and Cooper pairs. Introduction to BCS theory.
  5. Lattice systems: Bose- and Fermi-Hubbapop-contentrd models.
Course guide


  1. Physical Chemistry of surfaces
    • Introduction to surfaces
    • Structure of surfaces
    • Solid-liquid and solid-gas interphases
    • Characterization techniques
    • Applications in sensors and catalysis
    • Functionalization of nano- and microreactors
  2. Mechanics and Fluid mechanics at micron scale
    • Introduction to micromechanic and microfluidic behavior.
    • Biosensor structure
    • Design and simulation of the biosensor fluidic behavior
    • Design and simulation of the biosensor mechanic behavior
    • Case studies in bioengineering and comunications.
  3. MEMS microdevices applied to communication circuits
    • Introduction to MEMS micro-devices. Materials and structures.
    • Ohmic- and capacitive-contact micro-switches.
    • MEMS micro-switch electromagnetic simulation
    • Application of MEMS micro-switches to reconfigurable communication circuits.
    • Circuit simulation.
    • Experimental characterization of MEMS micro-switches.
Course guide


  1. Sources of Synchrotron and neutron radiation.
    • Continuous and pulsed sources.
  2. Safety in large facilities.
  3. Design of main devices in Sinchrotron and neutron sources:
    • focusing of photons and neutrons
    • dispersion and detection
  4. Design and use of special sample environments:
    • High pressure
    • high and low temperature
    • magnetic fields.
  5. Experimenal techniques available in large facilities.
    • Complementarity between experimental techniques
  6. Generation, storage and analysis of large facilities:
    • Experimental data
Course guide


  1. Project planning.
  2. Planning methods based on critical path.
  3. Precedence analysis, PERT and GANTT chart.
  4. Time and cost estimation.
  5. Risk identification and mitigation plans.
  6. Stakeholders communication management.
  7. Project execution management: earned value.
  8. Project closure: success criteria and lessons learned.
Course guide


  1. Basics of condensed matter
    • Microscopic constituents and effective interactions; condensed phases: normal and supercritical fluids, crystals, glasses, mesophases; classification and examples of transitions (first order, continuous, glassy); van der Waals theory and isomorphic states; miscibility and binary systems
    • Molecular disorder and dynamics; linear response theory, dielectric and mechanical spectroscopy, other experimental methods (thermodynamic and optical probes, scattering)
  2. Single-component systems
    • Small-molecule condensed phases; crystallization kinetics & polymorphism; structural glasses, ultrastable & aged glasses; orientationally disordered solids & plastic crystals; primary & secondary relaxations; charge conduction in molecular solids and liquids
    • Amorphous & semicrystalline linear homopolymers; ideal chain statistics and entanglement effects, entropic forces, Rouse modes and reptation; viscoelasticity, glass transition, and crystallization of linear polymers; branched polymers, gelation and rubber elasticity, affine network model for elastomers; conjugated and conductive polymers
    • Thermotropic liquid crystals (nematic, smectic, columnar) and liquid crystal polymers; optical properties and applications
  3. Multicomponent and aqueous systems
    • Polymer solutions: non-ideal chains, theta-solutions, hydrogels, swelling phenomena; superhydrophobic/hydrophilic, superolephobic, superamphiphilic, and self-healing polymer coatings; biopolymers, helix-coil and coil-globule transitions
    • Self-assembly in condensed matter: specific and non-specific interactions; block copolymers; colloidal systems (glasses, crystals, gels), surfactant-water systems, biomembranes, lyotropic liquid crystals, emulsions; semiflexible polymers & cytoskeleton
Course guide


  1. Introduction: the hydrogen atom
  2. Interaction between atoms and external fields (static and oscillatory)
  3. Fine and hyperfine structure. Selection rules
  4. Symmetries of the wave function
  5. Many-electron atoms. Thomas-Fermi model, and Hartree-Fock method
  6. Understanding the periodic table of elements
  7. Molecular structure and degrees of freedom
  8. Advanced spectroscopic techniques: infra-red, Raman, and nuclear magnetic resonance
  9. Laser cooling, manipulation and detection of ultracold dilute quantum gases
Course guide


  1. Mechanical properties of materials
    • Introduction to elasticity
    • Ferroelasticity. Landau theory of phase transitions
    • Microstructure
    • Structural phase transitions
  2. Optical and electric properties of materials
    • Polarization and polarization mechanisms
    • Ferroelectricity, pyroelectricity, piezoelectricity
    • Dielectric response to variable frequency electric fields
    • Optical response of materials
  3. Magnetic properties of materials
    • Diamagnetism
    • Paramagnetism
    • Ferromagnetism
    • Other types of magnetism: ferrimagnetism, antiferromagnetism and non-collinear ferromagnetism
  4. Magnetostructural coupling
    • Ferroic and muliferroic transitions
    • Magnetoelasticity
    • Metamagnetism
Course guide


  1. Physicochemistry of solutions
    • Introduction to inorganic chemical physics of electrolyte & nonelectrolyte solutions: Types of solutions.
    • Thermodynamics of solutions (entropy, free energy and chemical potential; phase diagrams).
    • Properties of water: The hydrogen bond, solubility of molecules in water, polar and non-polar solvents.
    • Electrical permeability of water.
    • Dissociation: acids and bases, protonation.
    • Properties of solutions: functional groups, hydrophilic and hydrophobic interactions; solubility; diffusion.
    • Colligative properties: boiling-point elevation, freezing point depression, osmotic pressure.
    • Surface tension, capillarity.
    • Water phase diagram and anomalies; aqueous electrolytes; non-electrolyte solutions.
    • Electrostatics for salty solutions: biopolymers (polyelectrolytes) and biomembranes in water; Poisson-Boltzmann equation, Debye-Hückel model, electric double layers, ion and proton conduction; transport properties.
  2. Applications to pharmaceutics, drug formulation, & biophysical pharmacology
    • Experimental techniques for electrolyte and non-electrolyte solutions
    • Small Molecules (drugs): HPLC, Chromatography, Mass spectroscopy, ICP-MS
    • Characterization of Nanoparticles: Molecular sizes (Dynamics light scattering, DLS), Surface charge (zeta potential, with conductivity measures)
    • Characterization of Biomolecules: chromatography, gel electrophoresis, Western Blot. Proteomics
  3. Physicochemistry of solids
    • Introduction to inorganic solid-state chemical physics (cohesive interactions; organic solids and salts)
    • Structural and mechanical properties of homogeneous solids
    • Non-miscible systems: morphology and properties of phase-separated materials
Course guide


  1. Basics concepts of crystallography
    • Translational order, unit cell, Bravais lattices.
    • Point groups, space groups, crystal systems.
    • Crystallographic planes, reciprocal lattice, Miller indices.
    • From crystal system to molecular structure and geometry: crystals with a base and molecular crystals.
    • Calculation and modelling of diffraction patterns from atomic and structure scattering factors.
    • Solid-state polymorphism of drugs and other organic molecules.
    • Second harmonic generation.
  2. Phase Equilibrium and phase transitions
    • Thermodynamic Potentials for hydrostatic pvT systems
    • Maxwell relations
    • TdS equations
    • General conditions for equilibrium
    • Fluctuations
    • Le Châtelier principle.
  3. Phase transitions and topological pressure-temperature phase diagram
    • Equilibrium conditions for hydrostatic pvT systems
    • First-order phase transitions: Clausius-Clapeyron equation.
    • Stability and metastability domains
    • High-order phase transitions.
    • Group-subgroup phase transitions.
    • Critical and triple points
    • Topological P-T phase diagram.
    • Calorimetry techniques.
  4. Landau theory for phase transitions
    • Landau Theory.
    • Order Parameter.
    • Ferroic phase transitions.
    • Long-range anisotropic interactions.
    • Self-accommodation.
    • Structural phase transitions.
    • Mechanistic and kinetic classification of phase transitions.
  5. Phases out of equilibrium
    • Glass state and glass transition
    • Dynamics and structural relation in the glass state
    • Pressure dependence of the glass transition temperature
    • Non-equilibrium phases and mesophases of drugs.
    • Dielectric spectroscopy.
  6. Binary systems
    • Thermodynamics of mixing, thermodynamic potential
    • Types of binary phase diagrams: eutectic, metatectic and peritectic
    • Solubility and miscibility
    • Metastable and unstable states
    • Nucleation vs spinoidal decomposition
Course guide


  1. Biological networks
    • Examples in systems biology (metabolic networks, interactome, regulatory and signalling networks)
    • Biological neural networks
    • Networks in ecology and epidemiology
  2. Complex spatio-temporal dynamics in biology
    • Oscillations, excitability, bistability
    • Synchronization in biological systems: neural networks
    • Spatio-temporal chaos: cardiac fibrillation
  3. Complex biosignal analysis
    • Deterministic and stochastic signals
    • Statistical properties
    • Nonlinear time series analysis
  4. Self-organization in biological systems
    • Morphogenesis
    • Self-assembly (protein folding, membrane formation)
    • Growth processes (chemotaxis, tumour growth)
  5. Collective motion and active matter
    • Flocking, swarming and herd behaviour
    • Cell migration
Course guide


  1. Introduction to Machine Learning
    • Fundamental problem of Machine Learning
    • Description of the inherent complexity of the problem
    • General approximations to the solution.
  2. Classical models of Neural Networks
    • Hopfield model
    • Recurrent Boltzmann Machines (BM) and Restricted Boltzmann Machines (RBM)
    • Learning with BM and RBM: gradient descent, Contrastive Divergence and variations
    • Single-layer Perceptrons (SLP): lineal regression, logistic regression, Rosenblat perceptron
    • Multi-layer Perceptrons (MLP)
    • Learning with MLP: Back-propagation
    • Convolutional Neural Networks (CNN): model, link with MLP and learning
  3. Deep Learning: link with classical models and modern learning techniques

Course guide


  1. Introduction. Discretization methods of the continuum; finite differences, finite elements and volumes, spectral methods.
  2. Weak formulation of differential equations. Galerkin and Petrov-Galerkin methods. Collocation. Application to the equations of Mathematical Physics and Engineering.
  3. The finite element method. Piece-wise Lagrangian approximation. Types and families of finite elements. Nodal and modal elements. Isoparametric elements. Interpolation error and types of convergence.
  4. Implementation of the finite element method. Meshing of domains. Triangulation software. Assembly of matrices and vectors. Quadrature formulas. Error estimation. Application examples in Matlab/Octave.
  5. Variational theory of the finite element method. Some results on Functional Analysis. Sobolev spaces. Elliptic problems. Lax-Milgram theorem. Céa's lemma.
  6. Time integration. Order of the integration schemes. Total discretization, method of lines, and operator splitting. Stability, consistency and convergence.
  7. High order methods. Spectral elements. Gaussian and Fekete meshes. High order methods in time.
  8. The finite element method for the Navier-Stokes equations. Different weak formulations. Saddle point problems and stable elements. The Stokes problem. Time integration via Stokes problems or projection methods.
  9. Finite element libraries. The FEniCS library.
  10. Introduction to finite volume and discontinuous Galerkin methods.
  11. Complements of numerical linear algebra and non-linear systems of equations. Continuation methods.

Course guide


  1. Monte Carlo integration: distribution functions and their sampling. Crude Monte Carlo and rejection methods. Improving efficiency: variance reduction methods. Multidimensional integrals and Metropolis sampling.
  2. Monte Carlo methods for the study of many-particle systems: discrete systems (Ising), continuous systems in different statistical collectivities. Finite-size scaling. Advanced Monte Carlo methods.
  3. Stochastic optimization: simulated annealing and genetic algorithms.
  4. Dynamic Monte Carlo: randowm walks and the diffusion equation. Fokker-Planck and Langevin methods. Brownian dynamics.
  5. Application of Monte Carlo methods to quantum systems. Wave functions for bosons and fermions. Variational Monte Carlo. Diffusion Monte Carlo. Path integral Monte Carlo for the study at finite temperature.
Course guide


  1. Multidimensional Hydrodynamics
    • The Lagrangian and Eulerian formalisms in CFD
    • The hydrodynamic Euler equations
    • Hydrodynamic codes addressed to Astrophysical simulations
      • Eulerian versus Lagrangian methods and codes
      • Explicit versus Implicit methods
    • The Smoothed Particle Hydrodynamics method
      • Interpolation
      • Variable resolution in space and time
      • Lagrangian SPH equations
      • Applications of the Eulerian equations
      • Heat conduction and mass diffusion
      • Viscosity
      • Application to shocks and rarefaction problems
      • Astrophysical applications
      • Other applications
    • Introduction to the multidimensional Magnetohydrodynamics with SPH
    • Future developments
  2. Astrophysical applications of Monte Carlo methods
    • Overview of basic concepts
      • Random numbers vs. pseudo-random numbers
    • Random number generators
      • Desirable statistical properties
      • Types of generators: a) linear congruential generator; b) multiplicative congruential generator; c) Tausworth generator
      • Good and bad generators. Improvement techniques
    • Transformation methods
      • Uniform distribution and linear transformation
      • Inversion technique
      • Box-Muller method
      • Accepting-rejecting method
    • Some applications of Monte Carlo methods in Astrophysics
      • Globular clusters
      • The Galaxy
  3. Spectroscopic data analysis techniques
    • Introduction to observational astronomy
      • Telescopes
      • CCD cameras
      • The electromagnetic spectrum
      • Introduction to spectroscopy
    • Data reduction
      • Bias images and debiassing
      • Flat-field spectra and flat-field correction
      • Extraction of one-dimension spectra
    • Calibration
      • Arc-lamp spectra and wavelength calibration
      • Flux standard spectra and flux calibration
    • Data analysis
      • Reduction and calibration of real spectra