Computer Science, Mathematical Statistics, Machine Learning, Large Scale Data Mining
We will consider highly qualified candidates working at the intersection between computer science, physics, information theory, and mathematics, who combine a strong theoretical background with an orientation towards research on processing huge amounts of complex data in the analysis of socio economic, technical, or biological. Candidates must have an excellent record of high-impact international publications. They should have demonstrated remarkable ability in leading research groups, as well as experience in conducting/coordinating international projects.
Preference will be given to candidates active at the intersection between algorithms, theory and applications, in the following fields: analysis and modeling of massive data structures; graph theory and random structures; analysis and modeling of complex networks; machine learning, large scale data mining.
Research Area: Computer Science and Applications