11 PhD grants (3-year Programme) are offered by the Department of Computer Science at the University of Cagliari. 1 of these is reserved to foreign candidates. Three more grants might be added for foreign candidates too.
Each grant amounts to 50,000 euros. For research visits abroad (maximum 18 months) the grant increases of 50%. Substantial extra funding is available for participation to international conferences, schools, workshops, and research visits.
The language of the PhD program is English. Please note that one grant will be awarded to carry out work within the domain of financial technology for the forecasts of stocks market indexes and shares (Robo-Trading, Robo-Advisory) and will be in collaboration with a spin-off of the University of Cagliari.
Students will have the opportunity to work in different research areas including Machine Learning, AI, Big Data, NLP and Natural Language Understanding, Semantic Web, Recommendation Systems, Data Science, Computer Vision, Complex Networks, Computational Geometry, Blockchain, Sensors and Pervasive Computing, Architectures and Portable computing.
Equal opportunities to all applicants will be provided.
Application procedure must be done online. Deadline for applications is 27th August at 12.00 Italian time (GMT+2).
If you are interested in working within the domain of AI, Machine Learning, Deep Learning and Deep Reinforcement Learning, Big Data, Natural Language Processing, Graph Theory, Recommendation, and Semantic Web, we are the contact persons at the Department. We have several collaborations with International, National Institutions and Companies and within several national and International (e.g. H2020) projects. Our lab is expanding and we always search collaborations with foreign institutions to maximize the opportunities of our PhDs.
Questions can be forwarded to us:
Diego Reforgiato Recupero, diego.reforgiato@unica.it
Salvatore Carta, salvatore@unica.it
This opportunity has expired. It was originally published here:
https://www.unica.it/unica/en/news_avvisi_s1.page?contentId=AVS123111