PhD in Artificial Intelligence, Data Science, Statistics, Mathematics or related fields. Strong skills in Bayesian networks and machine learning are necessary, as well as proficiency in English and strong R programming skills. Experience in neuroscience and climate science will be valued.
Description of Work:
The successful candidate will work at Computational Intelligence Group (http://cig.fi.upm.es/) at the School of Computer Science of the Technical University of Madrid in Madrid, Spain.
The main objective of the project is the research, development and innovation in learning Bayesian networks from data arising from complex spatio-temporal networks. In particular, we aim at contributing in algorithms for score-based spatio-temporal causal discovery (avoiding the drawbacks of constrained-based methods), both in stationary/nonstationary and nonlinear domains. Moreover, the models will be applied to cutting-edge problems in climate and neuroscience domains from data on a big scale.
This Project is in collaboration with Fundacion BBVA
Duration of contract: 15 months. From July 1, 2020 to September 30, 2021(gross) Salary: Up to €45000 per annum (full time), depending on skills and experience
Contact: Interested candidates should send their CV to Concha Bielza (mcbielza@fi.upm.es) and Pedro Larrañaga (pedro.larranaga@fi.upm.es)