Call for application

Admission requirements and topics

For admission requirements and application procedure please check the call in the "Downloads" area on the right.

Only the Italian version of the call is legally binding.

In order to be admitted in the School applicants must be in possess of a Academic title which grants access to a third level education programme (PhD) in the country it has been issued.

Deadline: May 20, 2019, hrs. 04.00 PM (Italian time, GMT +2)

The application must be completed and submitted by the above deadline, solely by the online system: https://www.unitn.it/en/apply/dott.

The application which you must select is "Doctoral School in Information and Communication Technology 35th cycle - First Call 2019"

Applicants who do not have an account at the University of Trento must register in advance at: https://www.unitn.it/account.

The application shall be subject to the payment of an application fee - non-refundable - amounting to € 15 to be paid by credit card, according to the instructions given in the application.

Applicants are advised to register well in advance with respect of the deadline because the issue of the username and password (sent via email), necessary to enter UNITN’s online services, may require up to 2 working days. 

The administration strongly recommends that applicants ensure that they have received the notification email confirming the definitive completion of the application procedure.
Applicants are asked not to wait until the last days prior to the deadline before submitting their applications.

During the filling out of the online application, applicants must choose which research area and no more than two project specific grants (reserved topic scholarships) within the area they are interested to apply for.   

 

Curriculum and scholarships

Curriculum

1: Computer Science

2: Telecommunications

Research Area

A

B

C

D

UNITRENTO scholarships

3

2

-

3

UNITRENTO - DISI reserved topic scholarships

- - -

1

DISI reserved topic scholarships

3

2

2

1

FBK reserved topic scholarships

7

3

5

2

OSRAM - DISI reserved topic scholarships

1

-

-

-

Positions without scholarship

-

3

1

1

UNITRENTO: University of Trento
DISI: Department of Information Engineering and Computer Science, University of Trento
FBK: Fondazione Bruno Kessler
OSRAM: OSRAM GmbH

Area A (Curriculum 1: Computer Science)

  • Computer Vision
  • Machine Learning
  • Natural Language Processing
  • Speech and Dialogue

Project Specific Grants (reserved topic scholarships)

Department of Information Engineering and Computer Science

  • A1 - Open-ended Learning for Social Robots (1 grant) » details 
  • A2 - Grounded Conversational Agents (1 grant) » details 
  • A3 - Conversational Modeling and Systems (1 grant) » details 

FBK

  • A4 - Deep Learning for Urban Environment (1 grant)  » details
  • A5 - Deep Learning, constraints and network topologies (1 grant)  » details
  • A6 - Incremental learning of abstract planning models via acting in a real environment (1 grant)  » details 
  • A7 - Bayesian reasoning for statistical relational learning (1 grant) » details 
  • A8 - End-to-End Automatic Speech Recognition (1 grant) » details 
  • A9 - Neural speech-translation (1 grant) » details 
  • A10 - Fast and high-precision 3D inspection and monitoring of non-collaborative surfaces (1 grant) » details 

OSRAM - Department of Information Engineering and Computer Science

  • A11 - Domain adaptation for people detection, re-identification and pose estimation (1 grant) » details 

Area B (Curriculum 1: Computer Science)

  • Embedded Systems
  • Cyber Security
  • Systems and Networks
  • Wireless Networking

Project Specific Grants (reserved topic scholarships)

Department of Information Engineering and Computer Science

  • B1 - Cyber ranges as a multi-domain platform for security research and training (1 grant) » details 
  • B2 - Next-generation Ultra-wideband Localization and Communication for the Internet of Things (1 grant) » details 

FBK

  • B3 - Programmable 5G systems (1 grant) » details 
  • B4 - Application-aware fog computing (1 grant) » details 
  • B5 - Stretchable antennas (1 grant) » details 

Area C (Curriculum 1: Computer Science)

  • Data Analytics and Management
  • Formal Methods
  • Human Computer Interaction
  • Knowledge Management
  • Social informatics
  • Software Engineering

Project Specific Grants (reserved topic scholarships)

Department of Information Engineering and Computer Science

  • C1 - Learning human behaviour from streams of personal data  (1 grant) » details 
  • C2 - Design and realization of a GDPR compliant data infrastructure (1 grant) » details 

FBK

  • C3 - Default in contextualized knowledge representation (1 grant) » details 
  • C4 - Fusion of remote sensing and citizen science information for geospatial city sensing (1 grant)  » details 
  • C5 - Formal and genetic methods for model-based testing of parameterized systems (1 grant)  » details 
  • C6 - Safety analysis for space and avionic systems and software (1 grant) » details 
  • C7 - Condition monitoring for predictive maintenance by integrating machine learning and background knowledge (1 grant) » details 

Area D (Curriculum 2: Telecommunications)

  • Distributed Sensing
  • Multimedia analysis
  • Pattern recognition
  • Remote Sensing and Radar
  • Signal processing 
  • Communication Systems 
  • Machine learning for signal and image analysis

Project Specific Grants (reserved topic scholarships)

University of Trento - Department of Information Engineering and Computer Science

  • D1 - Development of methodologies and automatic techniques based on artificial intelligence and machine learning for the analysis of satellite remote sensing images (1 grant) » details 

Department of Information Engineering and Computer Science

  • D2 - Development of methodologies and automatic techniques for the analysis of data acquired by planetary radars (1 grant) » details 

FBK

  • D3 - Design of methods for automatic analysis of sub-surface radargrams (1 grant) » details 
  • D4 - Satellite Image Time Series (SITS) analysis  » details