PhD Course (D.M.45)
Industrial Innovation
COURSE SUMMARY
The PhD course in Industrial Innovation is an interdisciplinary programme promoted by the departments of Engineering and Computer Science (DISI) and Industrial Engineering (DII) in collaboration with the Department of Economics and Management (DEM), the Department of Civil, Environmental and Mechanical Engineering (DICAM), the Department of Physics, and in agreement with the Bruno Kessler Foundation (FBK). Companies engaged in research and development are involved in both the design of the course programme and the activation of doctoral positions.
The programme aims to train experts specialised in technological and scientific innovation related to Industry 4.0, with competencies in the field of innovation management and related soft skills. Students will access training modules aimed at developing entrepreneurial and managerial skills, attracting public and private funding and in managing innovation processes. To deepen their knowledge of the industrial context, the doctoral student will spend at least 6 months of the programme at one of the companies supporting the doctoral project.
The course in brief
OVERVIEW
- Accessibility and assistance systems
- Artificial Intelligence
- Asset Allocation
- Autonomous vehicles and robots
- Bioinformatics
- Biomaterials and biomedical technologies
- CMOS image sensors and radiation detectors
- Coatings and surface treatments
- Computer Vision
- Cyber Security
- Data Science and Management
- Deep and Structured Machine Learning
- Distributed measuring systems
- Distributed Sensing
- Electronics
- Embedded Electronics and Computing Systems
- Experimental characterization of the mechanical behaviour and numerical modeling
- Finance
- High-strength glasses and ceramics
- Human-Computer Interaction
- Intelligent machine tools and machining processes
- Intelligent systems and instrumentation for the quality of life
- Language, Speech and Interaction
- Machine Learning and Intelligent Optimization
- Materials chemistry
- Materials for energy
- Measurement systems and sensor data fusion
- Mechanisms for space applications
- Microelectronics
- Microsensors
- Modeling and simulation of mechatronics system
- Modeling of the human movements
- Modeling, simulation and control of process
- Multimedia Signal Processing and Understanding
- Nanostructured materials
- Polymeric and composite materials
- Product innovation
- Remote Sensing and Radar
- Risk Management
- Signal Processing and Recognition
- Smart energy systems
- Social Informatics
- Software Engineering and Formal Methods
- Systems and Networks
- Systems on chip (SoC), energy harvesting and ultra-low power methodologies
- Wearable computing
- Wireless Networking
- Wireless sensor networks and cyber-physical systems
- INF/01 Informatics
- ING-INF/03 Telecommunications
- ING-INF/05 Information processing systems
- ING-INF/07 Electric and electronic measurements
- ING-IND/09 Energy systems and power generation
- ING-IND/10 Thermal engineering and industrial energy systems
- ING-IND/12 Mechanical and thermal measurements
- ING-IND/14 Mechanical design and machine construction
- ING-IND/22 Materials science and technology
- SECS-S/06 Mathematical methods of economy, finance and actuarial sciences
- SECS-P/08 Management
- SECS-P/10 Organization studies
- FIS/01 Experimental physics
- ICAR/09 Structural engineering
To apply for the PhD programme, you must have:
- a specialist or master's degree or a degree issued under the previous regulations;
- an equivalent academic qualification obtained abroad (master's degree) that allows admission to the PhD program in the education system or in the country of issue and that is considered suitable by the selection committee for the sole purpose of accessing the course.
Students selected by special committees for specific international mobility programmes in which the University of Trento participates may also apply.
The admission call indicates:
- admission requirements;
- deadlines;
- admission procedure;
- details of the funded positions;
- availability of scholarships.
For this doctoral course the following are available:
20 + 1 + 1 places;
10 + 1 scholarships;
10 + 1 non-scholarship places reserved for employees of companies engaged in relevant research and development activities.
The breakdown of the available places and the details of the funded positions are specified in the admission call.
For information on the scholarships, topic-specific places and the additional scholarship, see the details on the page indicated.
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