Teaching and training activities
The DipE project has led to the creation of the PhD Course in “Computational Methods and Mathematical Models for Science and Finance”, a course for students interested in research topics in Financial Mathematics, Numerical Analysis, Computational Physics, Computational Chemistry and Biology. Nine new PhD scholarships have been funded for the XXXV Cycle (academic year 2019-2020), 6 new PhD scholarships for the XXXVI Cycle (academic year 2020-2021) and 5 new PhD scholarships for the XXXVII Cycle (academic year 2021-2022). The new PhD programme has lent impetus to the research themes involved, partly thanks to the productive contribution of the students who took an active part in the activities and who also acted as a binding factor between the two groups of Informatics and Bio-Informatics.
Also thanks to the DipE, the Faculty of Sciences of the Scuola Normale has provided a strong impulse to the development of advanced lines of training in the Computational Sciences and Data Science, favouring their integration in the applicative sense with the other scientific and research areas present within it. The teaching and training activities regard the numerous courses offered within the PhD programmes (such as Numerical Analysis and Optimisation, Statistical and Machine Learning Models for Time Series Analysis, Quantitative Finance, Drug Discovery: from physico-chemical interactions to medicinal chemistry, Scientific Programming I and II, to mention but a few of the new PhD courses in Computational Sciences), further enhanced by an intense programme of seminars by visiting lecturers.
In addition, the DipE has enabled the funding of the organisation of schools in the field of the Computational Sciences and its applications, consolidating the research and training programme undertaken by the Scuola Normale. Particularly noteworthy is the organisation of the “School in Mathematical and Computational Aspects of Machine Learning” (7-11 October 2019) and of the first edition of the school in “Machine Learning of Dynamic Processes and Time Series Analysis” (26-27 November 2020).
Lastly, the hiring of a full professor in the s.s.d. INF/01 has further increased the teaching and training curriculum already present at the Scuola Normale, in particular with the introduction of three new courses: Artificial Intelligence, Explainable Artificial Intelligence and Introduction to Machine Learning for Bioinformatics and Life Sciences.