Master's Degree in Physics of Complex Systems
Degree data and benchmarks
Students
Data and description
2012-13 | 2013-14 | 2014-15 | 2015-16 | 2016-17 | 2017-18 | |
---|---|---|---|---|---|---|
New | 4 | 10 | 6 | 11 | 11 | 12 |
SIIU New | 4 | 10 | 6 | 11 | 10 | 12 |
Registered | 4 | 12 | 10 | 15 | 16 | 15 |
Graduates | 2 | 8 | 6 | 9 | 12 | 10 |
New students: these students are starting their studies from the beginning for the first time. They may have recognised credits or not.
New SIIU students: these students are starting their studies from the beginning, registering on a programme for the first time and, in accordance with SIIU criteria, may have fewer than 10 credits (for a Master's) or 30 credits (for an undergraduate programme) recognised. This set of students may also be referred to as the optimum new entry group.
Registered students: these students have an active registration on a programme for an academic year. This set of students may also be referred to as the total student population.
- Registration reservations are not included (due to the students awaiting a place at another university or credit recognition)
- Registration cancellations are not included
- Students with unpaid debts are not included
Graduates: these students have passed (passed or accredited) all credits required for the degree programme and have, therefore, finished their course regardless of whether they have requested their degree certificate be issued or not.
Entry Cohort
Data and description
2012-13 | 2013-14 | 2014-15 | 2015-16 | |
---|---|---|---|---|
Graduation Rate | 100% | 100% | 100% | 82% |
Drop-out Rate | - | - | - | 9% |
Final drop-out rate: the percentage of students from a new entry cohort that, without graduating, have not re-registered on the degree or any other programme, either at this university or at any other insitution in Spain, for two academic years in a row.
Graduation rate (RD 1393/2007) is defined as the percentage of students from an entry cohort that finish their programmes in the theoretical planned timeframe for the curriculum, or within an additional academic year. The reference population is the New Full-time SIIU Student Group.
Graduating Class
Data and description
2012-13 | 2013-14 | 2014-15 | 2015-16 | 2016-17 | 2017-18 | |
---|---|---|---|---|---|---|
Graduate Efficiency Rate | 100% | 96% | 89% | 91% | 94% | 98% |
The efficiency rate is defined as the percentage ratio between the total number of credits passed by students throughout the registered programme from which they have graduated, and the total number of credits they effectively registered for. The reference population is the optimum group.
Credits Taken and Passed
Data and description
2012-13 | 2013-14 | 2014-15 | 2015-16 | 2016-17 | 2017-18 | |
---|---|---|---|---|---|---|
Degree Success Rate | 100% | 100% | 100% | 100% | 100% | 100% |
Performance Rate | 91% | 93% | 88% | 85% | 93% | 91% |
Success rate: the percetage ratio between the number of passed credits and the number of credits taken for assessment.
Performance rate: the percentage ratio between the number of credits passed and the number of credits registered for.
Who directly oversees the quality of the degree programme?
Quality Assurance Commission
- Damià Gomila
- Tomàs Sintes
The Quality Assurance Committee (CGQ) gathers all of the information regarding the degree programme (survey reports, data, statistics, complaints, suggestions, etc.) and analyses them. Here, you can see the regulations and duties of the Quality Assurance Committee (CGQ).
Commitment to quality
Suggestion/complaint form
Procedures for handling and revising incidents, complaints, and suggestions
Planning improvement measures
Accountability and transparency
Link to the Register of Universities, Centres, and Degrees (RUCT)
Procedure | Document | Date/Year |
---|---|---|
Monitoring | Annual follow-up and internal assessment report (2017-18) | 19/06/2019 |
Monitoring | External follow-up report (2016-17) | 24/09/2018 |
Monitoring | Annual follow-up and internal assessment report (2016-17) | 23/03/2018 |
Monitoring | Annual follow-up and internal assessment report (2015-16) | 23/06/2017 |
Accreditation | Council of Ministers' resolution | 14/06/2016 |
Accreditation | Final accreditation report | 26/04/2016 |
Verification | First official university statement modification | 28/01/2014 |
Verification | Final verification report | 28/06/2012 |
Verification | Official university degree statement | 08/05/2012 |
Monitoring | External follow-up report (2013-14) | 2013-14 |
Monitoring | Annual follow-up and internal assessment report (2013-14) | 2013-14 |
Monitoring | Annual follow-up and internal assessment report (2012-13) | 2012-13 |
End of master projects
- A market model for exploitation and cooperation using the Minority Game
- Constructive role of plasticity rules in reservoir computing
- Data analysis and modeling of patient flow in emergency services in hospitals
- Detecting the topological phases of the Kitaev model via complex network analysis
- Information processing using optoelectronic delayed systems: influence of an additional delay
- Modelling Residential Segregation for Economical Reasons
- Multilayer reservoir computing to overcome the memory-nonlinearity trade-off
- Network description of dynamical systems: The clustering coefficent
- Noisy voter model with partial aging and anti-aging
- Phase space reconstruction of semiconductor laser dynamics using reservoir computing
- Price Dynamics in a Model of Leveraged Based Investment
- State transfer in Open Quantum Systems
- Stochastic games on Networks: a study on Prisioner’s Dilemma and Public Good Games
- Studying national and international migration flows with Twitter data
- Study of cluster crystals with two different stochastic models and two different repulsive potentials
- Vegetation Front Dynamics
- A Consumer-Resource Description of Public-Goods Production in Microbes
- Active cluster crystals with Vicsek-like alignment interaction
- Application of a neural mass model to study phase-amplitude coupling
- Autonomous dynamical systems based on hardware implementations of delay-reservoir computers
- Cluster Crystals under an external flow
- Collective motion of Brownian walkers in a Birth-Death gradient
- Complex Photonic Systems for Post-Processing Communication Signals
- Front motion in a non-local Fisher-Kolmogorov-Petrovskii-Piscunov (FKPP) equation
- Memory in Idiotypic Network Dynamics
- The noisy voter model with contrarian agents: a theoretical and computational study
- Dynamics of attracting Brownian particles
- Exact Computation of Percolation Cluster Sizes in Finite Networks
- Field theory for recurrent mobility
- Financial contagion in the interbank market
- Improved detection of collective rhythms in multi-channel electroencephalography signals
- Modelling Quorum-Sensing mechanisms in bacterial populations
- Multiple options noisy voter model: application to European elections
- Searching Chimera States in the Nonlocal Complex Ginzburg Landau Equation
- Sincronització quàntica en sistemes optomecànics
- Sobre la forma de l'espai semàntic. Què podem deduir de les propietats estadístiques de llarga escala de textos?
- Synchronization in a Neural Mass Model
- Universality of the fundamental diagram in pedestrian dynamics. A study based on social force models.
- "Dynamics of vascular branching morphogenesis"
- "Photonic Reservoir Computing: the role of the Mach-Zehnder modulator"
- Cooperative Epidemic Spreading
- Inelastic effects on thermoelectric transport through Coulomb systems
- Network properties of genotype-phenotype mappings
- Neural circuit in the hippocampal region
- Noise Effects in Kerr Frequency Combs
- Pattern formation in clonal planrs
- Robustness of plant-pollinator mutualistic networks to phenological mismatches
- "Models of mobility"
- "Statistical mechanics of multilayer networks"