How did it come about?
BCAM, through its research work, has a clear strategic line towards the international community, as it seeks to promote mathematical research to identify, understand and solve society's challenges.
Due to this need, the BCAM Project Office emerges. The main objective of this Office is to obtain the necessary resources to provide support for the participation of researchers in regional, statal, and European programs.
Areas of action - What is our function?
This Office offers a comprehensive service that covers a project's life cycle, from identifying funding opportunities to planning, execution, follow-up, and closure of projects, including efficient economic and administrative management. Accordingly, support is offered to research staff in the following aspects:
Connecting ideas with funding opportunities and professional career development guidance.
Design and presentation of proposals and their associated documentation.
Support in the search for agreements and contracts.
Project monitoring and control.
Project justification and audits (if required).
Any other management related to the development of the project.
Our team - Who are we?
This office has a transversal nature, and it is made up of a multidisciplinary team, formed by three professionals with different profiles. They work with the common goal of helping and facilitating the work of the center's scientific team in terms of project management and they are supported by the rest of BCAM's administrative team.
Miguel Ángel Benitez Lozano- Project Manager
Ainara Gonzalez Blanco- Project Manager
Nerea Mena Bikandi- Project Officer
People attraction management:
Idoia Hernandez- Management Assistant
June Fuentes- Internship
Economic justifications and audits:
Irantzu Elespe- Management Assistant
Asier Sojo- Management Assistant
Josu Diaz- Internship
Legal aspects of the programs:
Oriana Elejalde- Management Assistant
Communication and dissemination of the programs:
Olatz Aretxabaleta- Community Manager
Esti Gutierrez- Community Manager
BERC Programme 2022-2025
Open Superconducting Quantum Computers
The OpenSuperQplus consortium is a structured partnership aiming at large-scale European quantum computers in the superconducting platform.
Chemistry informed machine learning in emulsion polymerization processes and products
Laboratories for Trans-border Cooperation-Transmath
The Laboratories for Trans-border Cooperation (LTCs) are a formula for collaboration that have been developed since 2015 in the frame of the Campus Euskampus-Bordeaux.
Multiscale Inversion of Porous Rock Physics using High-Performance Simulators: Bridging the Gap between Mathematics and Geophysics
The main objective of this Marie Curie RISE Action is to improve and exchange interdisciplinary knowledge on applied mathematics, high performance computing, and geophysics to be able to better simulate and understand the materials composing the Earth's subsurface.
The Intergovernmental Panel on Climate Change (IPCC) has concluded that climate change is now indisputable and is having irreversible consequences.
Desing of a Virtual Blood Rheometer for Thrombotic Process Characterization
Early-stage diagnosis and continuous non-invasive monitoring of coagulopathies is a challenging problem that has been exacerbated by the COVID-19 pandemic.
Early Prognosis of COVID-19 Infections via Machine Learning
The 2020 COVID-19 outbreak has revealed infections that result in particularly distinct outcomes: certain patients remain asymptomatic during the infection, others experience moderate symptoms for a few weeks, while still others suffer acute or even critical complications.
High-performance aerodynamics and aeroacoustics simulations of the new generation of high-speed gas turbines via high-order Galerkin methods
The main goal of this project is to perform efficient and accurate simulations of the turbulent compressible flow and generated noise on the new high-speed gas turbines at operation conditions, with the aim of supporting engineers in the design of efficient engines and effective noise reduction solu
Bayesian Models and Algorithms for Fairness and Transparency
EU's GDPR prescribes that ""Personal Data shall be processed lawfully, fairly, and in a transparent manner."" The vision of this BayesianGDPR project is to integrate into automated machine learning systems using a novel Bayesian approach, in a transparent manner, the legal non-discriminatory princip
Space-time DPG methods for partial-differential equations with geophysical applications
The main objective of this project is to design stabilized space-time adaptive techniques based on Discontinuous Petrov-Galerkin (DPG) methodology for the simulation of transient Partial Differential Equations (PDEs), with special emphasis on advection-dominated- diffusion and wave propagation probl
Disruptive materials, technologies & approaches to unravel the role of Astrocytes in brain function and dysfunction: towards to Glial interfaces
The past four decades demonstrated that non-neuronal cells, called astrocytesare emerging as crucial players for brain function & dysfunction.
Analysis, Design, And Manufacturing using Microstructures
ADAM^2 aims at questioning five decades of traditional paradigms in computer aided design CAD.
Measuring ideals in a singularity
This proposal concerns singularities arising in the solution spaces of systems of polynomial equations.
Spectral theory and PDE: Real and Fourier Analysis
Harmonic analysis meets inverse problems
Advanced Numerical Methods and Neural Networks for Structural Health Monitoring of Offshore Wind Platforms
Be a Better digital Fire-Fighter
Development of novel mathematical and experimental methodologies to control neuronal activity and dissect spatio-temporal neuronal codes
Subproject 2 is divided in three different lines: phase response functions, estimation of model parameters and synaptic conductances and mapping multi-time scale models to macroscopic descriptions.
Ensemble forecasting for predicting wildfire propagation
The main goal of this project is the formulation of a stochastic dynamic prediction theory for ensemble forecasting of wildfire propagation. In spite of the fact that ensemble forecasting is a successful technique in weather prediction, its formulation for wildfire propagation is not at all a merely
MAnufacturing of CuRved Objects via Path-desIgn of cuSTom-shAped toolS
MACROPISTAS aims at questioning of few decades of traditional paradigms in 5-axis flank CNC machining by performing cutting-edge research in geometric modeling, mathematics, and manufacturing.
Liquid Crystals and interactions
The world of materials is undergoing a revolution and its main drivers are the complex materials that have a special composition at small scales, exhibiting microstructure.
Real-time Inversion using Deep Learning Methods
DEEPINVERSE project focuses on the numerical real-time inversion of wave propagation problems governed by Partial Differential Equations (PDEs) utilizing Deep Learning (DL) algorithms.
Geometric numerical integrators fr quantum problems, celestial mechanics and Monte Carlo
This subproject constitutes part of the coordianted proposal GEOMETRIC NUMERICAL INTEGRATORS FOR QUANTUM PROBLEMS, CELESTIAL MECHANICS AND MONTE CARLO SIMULATIONS (GNI-QUAMC), devoted to the design, analysis, and implementation of special purpose geometric numerical integration schemes, with particu
Unifying data processing via probabilistic transformations
The project main goals are to establish a theoretical unifying framework for data-driven problems (DPs), and to develop probabilistic data processing techniques (DTs) that effectively exploit data in a unified manner.