We are glad to announce that we have launched a series of projects related to different areas of applied mathematics. We are looking 2 research technician and 3 postdoctoral fellows to collaborate in those projects.
Research technician in supervised classification techniques
Research technician in Data Science in the Knowledge Transfer Unit
“Machine learning for COVID-19 predictions” deals with the development of supervised classification techniques that use electronic health records to predict evolution of COVID-19 infections.
Statistics (regression methods, time series, survival analysis, multivariate analysis, clustering methods), Machine Learning techniques and optimization.
Postdoctoral Fellowship in Biomathematics
Postdoctoral Fellowship in Applied Statistics
The topic to work on will be Biomathematics with the Mathematical and Theorical Biology Group Research Line Leader. We Seek a highly motivated and skilled person, able to work effectively as part of the MTB team. The PhD degree in applied mathematics, mathematical biology, physics or related disciplines will be a plus.
This project is titled “Fair Learning in Health” and deals with the development of mathematical models aimed at detecting and ensuring non-discriminatory and fair decisions based on artificial intelligence (AI) algorithms. Special focus will be placed on health applications.
Postdoctoral Fellowship in Applied Statistics - COVID19
Mathematical/statistical methods and computational tools for modelling the transmission dynamics of SARS-Cov-2 with a special focus on the prediction of health care resources. The combination of mechanistic models and Bayesian inference for uncertainty quantification and the development of efficient Markov Chain Monte Carlo (MCMC) samplers and numerical algorithms for the real-time use of the results.
