PhD Scholarships in Computer Science at the Free Univ. of Bozen-Bolzano (Italy)

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PhD Scholarships in Computer Science at the Free Univ. of Bozen-Bolzano (Italy)

Enrico Franconi
PhD Scholarships in Computer Science at the Free Univ. of Bozen-Bolzano (Italy).

The Free University of Bozen-Bolzano was founded in 1997 as a multilingual (English, German, Italian) internationally oriented institution.

A public competition for the allocation of PhD positions in the Faculty of Computer Science will be opened on the 6th of May 2016, for 12 places, of which 9 places will be covered by grants (17,000€ per year). The deadline for submitting the application (admission/pre-enrolment to the 32nd PhD cycle) via <> is the 8th of June 2016.

PhD students are expected to work full-time on their research during the period of the PhD studies, which lasts three years. An additional support is given to spend a period of 6-12 months at an international research center. The official language of the programme is English, and it is expected that students are able to write and speak fluently in English.

The PhD study programme places an emphasis on research. PhD candidates are strongly advised to look at the three areas (listed below) which are the focus of the research at the Faculty of Computer Science, and to get in contact with their desired research area before applying. The Selection Committee ranks PhD students based on a comparative assessment of the merits and qualifications of applicants, taking into account also feedback from potential supervisors in the selected research area.



Logic-based languages for knowledge representation
Intelligent access to data
Semantic technologies
Information integration
Data-aware process modelling, verification, and synthesis
Business process monitoring, mining, and conformance
Temporal aspects of data and knowledge
Extending database technologies
Visual and verbal paradigms for information modelling and exploration
Reasoning with Uncertain and Imprecise Knowledge

The KRDB Research Centre for Knowledge and Data (web page: <>) was founded in 2002, and it currently comprises about 30 researchers, including PhD students. The research activity is focussed on two main areas: (1) intelligent data and information management, with emphasis on modelling of data and on the challenges related to modelling and dealing with structured, complex, and big data; and (2) business processes and data, with the aim of studying the entire process lifecycle including the modelling of business processes and organisations. The KRDB Centre is widely recognised as one of the internationally leading groups in knowledge representation research, with a synergy between foundational research and application-oriented research. KRDB contact person: Enrico Franconi <[hidden email]>.


Spatial and temporal databases
Approximation techniques in databases
Query optimisation in databases
Cooperative interfaces for information access and filtering
Data mining techniques for preference elicitation and recommendation
Cloud computing and big data
Agile development and human aspects of software engineering
Software startups and lean startup methodology
Design based hardware engineering
Technology enhanced learning
Interaction design

The research activities in the area of database and information systems engineering focus on key aspects of applied computer science, including data warehousing and data mining, the integration of heterogeneous and distributed databases, time-varying information, data models, and query processing. The research approach is primarily constructive in its outset, and it includes substantial experimental and analytical elements. The development activities cover the design of data models and structures, and the development of algorithms, data structures, languages, and systems. The experimental activities verify real world artefacts with the help of prototypes and simulations. The analytic activities include the analysis of the algorithmic complexity and the evaluation of languages. The main goal is theoretically sound results that solve real world problems.


Empirical software engineering
Mining software repositories
Software reliability and testing
Automatic improvement and empirical investigation of software quality attributes
Recommendation systems in software engineering
Software system behaviour

The research topics in software engineering are focused on the empirical and quantitative study of innovative models for software development. The target analysis techniques include both traditional statistics, and new approaches, such as computational intelligence, Bayesian models, and meta-analytical systems. The innovative software development techniques include (a) methods based on lean management, such as agile methods, with a specific interest for benchmarking and identification of defects, and (b) open source development models, with specific attention for self organising systems and the analysis of the resulting quality aspects.