ICMAT – CSIC
Modeling and simulation
- Discrete event simulation.
- Monte Carlo simulation (for optimisation, inference,…).
- Chemical kinetics.
- Valuation of financial products and their risks, portfolio management.
Statistics and Big Data
- Statistical advice and data analysis.
- Time series forecasting.
- Customer, market and product studies.
- Risk and financial analysis.
- Bayesian statistics.
- Machine Learning.
- Biostatistics, epidemiology.
- Applications in the field of health.
- Quality control and reliability.
- Production, process and stock control.
- Statistical applications for industry or public administrations.
- Product optimization.
- Process optimization.
- Stock optimization.
- Resource optimization.
- Optimal decision support.
- Optimization of industrial and business processes.
- Bayesian optimization, decision analysis, risk management, stochastic optimisation,…
- Automatic learning.
- Neural networks.
- Bayesian networks.
- Machine learning.
- Deep learning.
- Programming in scientific languages: Fortran, C, C++, Pyton, Matlab, R.
- Development of software packages.
- Parallelisation of algorithms.
- GPU programming.
- Distributed computing.
Areas of experience:
Challenge 1: Health
- Visualisation, processing and analysis of medical images. Characterisation of false positives. Learning models using large databases (machine/deep learning).
- Disease prediction models, causal inference in medicine, …
Challenge 3: Energy
- Forecasting and planning of energy production for domestic or industrial use.
- Optimization of the planning of the expansion capacity of energy generating elements and their transmission.
- Decision-making assistance in energy processes.
Challenge 5: Environment
- Simulation, optimization and control of production and distribution processes.
- Integral optimization of product and goods supply chains.
- Supply chain security, cybersecurity in the supply chain.