PhD Programme in Computer Science
The PhD Programme lasts three years and the official language of the programme is English.
PhD students are expected to work full-time on their research. During the PhD, it is advisable to spend a period of 6-12 months at a National or International research center.
Candidates are strongly advised to contact their desired research centers at the Faculty of Computer Science before applying. This way, they can obtain a clear idea of the specific research carried out at the Faculty.
The Selection Committee selects PhD students based on a comparative assessment of the qualification of applicants, taking into account also feedback from potential supervisors, especially those who have grants available to support the PhD students, and determines the winners based on the merits of each candidate.
The Selection Committee also selects those candidates who are qualified to start a PhD program at the Free University of Bozen/Bolzano, but who cannot be admitted for lack of space. Should a selected winner not accept the position, such candidates will be next in line for the position.
It is expected that students are able to write and speak fluently in English.
The PhD study programme places an emphasis on research. A primary goal of the course is to impart to candidates the capacity to solve complex problems by independently applying technical and scientific methods.
This is achieved by immersing the candidates in activities that present specific demands such as:
- to understand complex scientific work on the current state of the art in computer science;
- to contribute to the work of the research group, which is equally characterised by innovative ideas as well as thorough expertise;
- to develop his or her own approaches to research and to elaborate them as far as possible in order to achieve new results;
- to work in an international field and to exchange and to disseminate scientific findings.
Upon successful completion of the degree of doctor of computer science, the graduate should exhibit the following skills and expertise:
- Substantial problem-solving abilities: Graduates take on complex problems with an innovative approach, with which they are familiar through their understanding of the technical scientific literature, and develop new instruments for problem-solving independently.
- The capacity for the communication and dissemination of results in the scientific field: The dissemination of scientific results is a substantial component of every activity in scientific sectors and the IT-industry. Graduates must therefore acquire skills in both written and verbal presentation of technical scientific topics: they must be capable of communicating their findings in writing, through scientific essays and papers, as well as verbally, in lectures.
- Organisational Abilities: The activity of a doctor in computer science consists in large part of studies and investigations. During his or her studies, the graduate student learns, without precise working organizational specifications. Graduates must be able to organize their activities both individually and within their research groups, as well as to coordinate study and work. This last point refers to the individual student, his or her doctoral work, as well as students and other co-workers on research projects.
- A thorough and comprehensive knowledge within the field of computer science, covering theoretical and formal aspects such as technology and methodologies.
Research in the Faculty of Computer Science is focused on three areas that are treated on a long-term basis by research groups whose members collectively examine topics related to each of the three research areas.
The research areas, with a selection of topics, are:
Databases and Information Systems
- Management and analysis of large data sets
- Temporal data models and databases
- Data evolution and integration
- Approximation techniques for large databases
- Machine learning techniques for searching and selecting information
The research activities in the area of database and information systems 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 artifacts 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.
Knowledge Representation and Databases
- Logic based languages for knowledge representation
- Intelligent database access
- Foundations of controlled natural language
- Temporal aspects of data and knowledge representation
- Extending database technologies
The research topics in knowledge representation are focused on foundational and practical aspects of knowledge representation technologies applied to information systems. The whole life cycle ranging from the design to the deployment of such technologies is covered: the conceptual modeling of various types of knowledge, the linguistic and logical aspects of knowledge, the integration of heterogeneous knowledge sources, including information coming from the Internet, the usage of knowledge to support the intelligent retrieval of information, and the usage of knowledge to create virtual services on the net.
- Agile methodologies, lean management, and open source
- Measurement and assurance of software quality, reliability and development
- Distributed computing and distributed service-oriented architectures
- Information technology and business alignment
- Component-based development and reuse of software
- Cooperative systems and interoperability of software
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 organizing systems and the analysis of the resulting qualit
The doctoral works treat topics from the three research areas that develop from the ongoing work of the groups.
The following list contains possible topics for doctoral work:
- Analysis of the trust factors in the Open Source Development process
- Analysis of the introduction and usage of Open Source software in the Public Administration
- Data collection and analysis for IT business alignment
- Integration and interoperability of mobile and location-based web services
- Visualization techniques for the evolution of software metrics
- Analysis of source code evolution in industrial and Open Source environments
- Integration and optimization of cooperative systems
- Medical data mining
- Temporal pattern recognition in medical data
- Multi-dimensional temporal OLAP
- Time varying geographic information systems
- Database cleansing
- Lossless database evolution
- Querying semi-structured databases
- Context-aware computing
- Adaptive recommender systems
- Ontology-Based Data Management: from Theory to Practice
- Query Processing in Expressive Description Logics
- Query Answering under Access Limitations
- Natural Language Access to Ontologies
- Integration and Composition of Web Services
- Multilingual Access to Library Catalogues
- Multilingual Interactive Question Answering
Doctoral candidates can furthermore specify their own topics together with their designated supervisor, as long as they remain related to the research areas outlined above.
The current Information Technology job market requires specialists, advisors and researchers with technical training in the field who are capable of working in a competitive international field.
The goal of the doctorate programme is to train scientists with solid expertise as researchers and specialists to work both in the academic field and in the IT sector.
A short overview of some career possibilities for specialists with a Doctorate in Computer Science follows below:
- University Researcher/Professor: Understanding of scientific topics, both in theory and practice, as well as the ability to find independent ideas and solutions for scientific problems are critical to this job description. The capacity of scientific communication, both written and verbal, is fundamental for high quality instruction and effective dissemination of research findings. In addition, a Doctor of Computer Science must take on a responsibility for the organisation of research projects in the field, for activity planning and coordination of work by students and researchers.
- Researcher in the IT Sector: A Doctor of Computer Science, as in an academic setting, will find high demand for his or her technical knowledge and expertise in scientific research, communication and the organisation of research work.
- Business Consultant, particularly in the IT Sector: In this field, the Doctor of Computer Science makes use of his or her training in problem solving, even in fields outside the purely technical ones. The Doctor of Computer Science plays a crucial role in finding means to solve problems in areas lacking structure. In such cases, a problem-solving approach must be developed for each individual case, relying on advanced modelling techniques.
- Management in the IT Sector: As an industrial manager, the Doctor of Computer Science performs complex tasks in project activity in the field of IT consultation. In addition to management qualities, technical expertise is necessary in order to guide decision-making in the proper direction and to solve problems in various areas.
- Entrepreneur in the IT Sector: In this field, the Doctor of Computer Science uses his or her ability to work independently, as well as to co-ordinate and manage others’ work. Comprehensive technical expertise in data processing provides inestimable advantages over the competition.