APPLIED DATA SCIENCE AND ARTIFICIAL INTELLIGENCE - PNRR

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Academic year 2024/2025
Department of Mathematics and Geosciences
Università degli Studi di Trieste
EQF level: 8
40° cicle
Field of study: natural sciences, mathematics, physics and statistics engineering and engineering trades
Place of teaching
trieste (TS), italy
Attendance methods
Full time
Languages in which the course is held
English
Cost
Free course
Scholarships
5 
Deadline (Expired)
22 July 2024

Course contents

The PhD Programme aims to train researchers with a thorough scientific preparation in the methodological foundations (informatics, mathematics, statistics) of data science and artificial intelligence, as well as their applications in various domains. The reference application areas include medicine and life sciences, industry 4.0, society and economics, data-driven science, with particular attention to their impact on the territory and society. The training in the first year includes education on the fundamentals and applications of data science and AI, including some ethical and legal aspects, as well as courses on organizational aspects of research and analysis of the state of the art. PhD students will be made aware of the principles of research reproducibility and FAIR data. The education will be personalized based on the student's previous study plan and the research topic pursued by the doctoral candidate. In the second and third years, scientific activity will be developed, potentially including a period of stay at internationally relevant research institutions. Common aspects of the training include a multidisciplinary theoretical-experimental approach, which is a qualifying aspect of both research and interaction with the territory and the productive world. PhD students will be given the opportunity to develop their communication skills: specific courses will be offered and their participation in educational and dissemination activities will be encouraged, both in scientific conferences/workshops and in public events. The main training goal is to prepare professionals in theoretical and applied research at an excellent level on the international stage.
Page of the course on the University's website

Teaching

Place of teaching
trieste (TS), italy
Attendance methods
Full time
Compulsory attendance
Languages in which the course is held
English

Admission requirements

Type of degree required
2nd Level Degree
Field of study
education, information and communication technologies (icts), architecture and construction, engineering and engineering trades, agriculture, forestry and veterinary, health and pharmacy, sports sciences and physical education, arts and design, humanities and literature, foreign languages, politics, social sciences and communications, psychology, economics, law, natural sciences, mathematics, physics and statistics
Foreign language skills
English
English (level of knowledge required: CEFR B2) tested in the interview
Other educational requirements
An Italian degree known as “Laurea specialistica/magistrale” or a degree awarded prior to approval of Ministerial Decree D.M. no. 509 of 3rd November 1999, as amended by D.M. no. 270 of 22nd October 2004 - awarded by 31st October 2024;
A foreign academic qualification - unless recognized as fully equivalent to an Italian degree - which is comparable for its duration, level and academic field to the Italian degree granting access to the PhD Course, and awarded by 31st October 2024.

Admission

Deadline
22 July 2024
Available places
5
Admission
Admission selection
Qualifications + interview
Cost
Free course
Scholarships
5
For details on places and scholarships see the link: https://portale.units.it/en/research/phd/programmes/artificial-intelligence

Employment opportunities

ADSAI PhD Graduates can pursue an academic path in research and teaching in the disciplines of the PhD Programme (statistics, computer science, mathematics). More generally, they can contribute with the tools of data science and artificial intelligence in research areas where they can be relevant. Their attention to practical aspects, also in close connection with public and private bodies operating in these areas, will enable PhD graduates to leverage the tools of data science and artificial intelligence in operational contexts within public or private organizations: companies, research institutions, public administrations. The close connection with numerous local institutions and companies is likely to promote the integration of PhD graduates into operational environments, both through numerous themed scholarships co-financed by companies and institutions and through their collaboration on educational projects.
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