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EURAXESS

Phd 2023/24 in DATA SCIENCE

Details

Deadline
Research Field
Professions and applied sciences
Funding Type
Funding
Career Stage
First Stage Researcher (R1) (Up to the point of PhD)

About

Outline

The availability of huge volumes of data, basically characterized by the increasingly extensive and pervasive use of digital technologies, leads the ongoing revolution in many areas of social, economic and industrial reality, posing new challenges to the scientific and technological research in Computer Science, Artificial Intelligence and in several other disciplines, from Physics to Economics, from Medicine to Human Sciences. In this context, the accessibility and processing of large amounts of data, both in centralized and distributed systems, their usage in the design and implementation of complex decision-making models, favors the study and development of autonomous systems in different fields (from mission-critical applications to the studies of natural and social phenomena, the prediction of economical dynamics as well as the diagnostics and planning in medicine or in industrial robotics).



The PhD in Data Science is aimed, in its markedly interdisciplinary nature, to train, at the highest level, experts able to conduct research to understand and master the mathematical, statistical and computer science methodologies of data analysis and processing as well as the underlying technologies supporting applications in a wide variety of of scientific, industrial, economic, medical and social contexts.



The reasons for a new PhD program in Data Science are many and significant. First of all, the offer in Central Italy of a doctoral training on these topics is still quite limited, but at the same time it is confronted with an increasing demand for experts in Data Science. This training should be understood with a characterization focused on mathematical-computer science skills, then a strong scientific-technological vocation, properly integrated on established statistical, economic, social and linguistic principles, thus able to give answers to the dynamics of this area of expertise that is very accelerated and strongly interdisciplinary and culturally heterogeneous.



The School of Doctorate represents the indispensable ground for a wide range of students of Computer Science, Computer Engineering, Economics, Physics, Mathematics and not only, at our University of Tor Vergata. Today such students apply and succeed (according to various data sources) at other Schools. These students are attracted by initiatives in Data Science because in them is clear and dominant the role played by the computational knowledge, the strong scientific character of the educational objectives and the diversified potential applications: from Physics to Economics up to Social Sciences.



It is interesting to note that many of the courses mentioned here, for example, the Master Degree Courses in Computer Science at the Department of Business Engineering, which have a large number of students, unlike other courses are not decreasing in number of enrolled students. This phenomenon is both cause and effect of the centrality that the themes of culture and digital transformation play in the industrial and social spheres of our country. These processes are at the basis of the growing appreciation received by the students who choose these studies and will also be the main objective of several development and innovation activities related to the National Plan for Recovery and Resilience from which the offer of the Doctorate described below cannot disregard.

What is funded

4 PhD sholarships

Duration

3 years

Eligibility

See https://phd.uniroma2.it/web/DATA-SCIENCE_nD1028.aspx

Organisation

Organisation name
University of Rome "Tor Vergata"
Organisation Country
More Information

Attachments

Disclaimer:

The responsibility for the funding offers published on this website, including the funding description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.