** Apologies for cross-posting **

** Please forward to anybody who might be interested. **

The University of Deusto invites applications for several PhD projects 
to be performed in DeustoTech. Deusto Institute of Technology 
-DeustoTech- (http://deustotech.deusto.es/) located in Bilbao (Spain), 
is a Research Institute of the Faculty of Engineering at the University 
of Deusto, and was created with the mission of promoting research and 
postgraduate training in Information Technology and Communications (ICT) 
through the participation in research projects of interest to society 
and industry. DeustoTech is looking for promising young researchers in 
the area of Artificial Intelligence. The positions are directed to 
master graduates and they are intended to offer three years fellowships.

*Grant summary*

The grants will have duration of 36 months, with annual renewals. Each 
12 months the performance of the doctoral student will be evaluated to 
check if he/she achieves the PhD research goals stablished for the 
period. The exact amounts awarded will be established by the University 
of Deusto. In the last year call, the annual gross salary was 16,6380€ 
for the first two years and 17,827€ for the third year. The application 
is open to worldwide research applicants.

*Research topics*

Deusto Smart Mobility (http://mobility.deustotech.eu/), is a 
high-performance research team that aims to contribute to a more 
sustainable, safe and fair mobility through Artificial Intelligence and 
Pervasive Computing. Applicants should choose four of the following 
topics and indicate their order of preference. You can find more details 
about each of these topics in the next link: 
https://docs.google.com/document/d/1e5Dj-Wk4Ta0pXge84hWURpDPRl8vw-pYSriR6lcyvY8/edit?usp=sharing 


1.    Deep Learning and Explainable Artificial Intelligence for Mobility 
Applications
Contact: Enrique Onieva ([log in to unmask])
2.     Optimization methods for sharing mobility scenarios
Contact: Enrique Onieva ([log in to unmask])
3.     Concept drift detection and adaptation methods applied to traffic 
forecasting tasks
Contact: Enrique Onieva ([log in to unmask])
4.     ML4PYMES: New AutoML methods for small and medium-sized companies
Contact: Juan Angarita ([log in to unmask])
5.     New AutoML methods for the sustainability of the Food Industry 
using non-conventional data sources
Contact: Juan Angarita ([log in to unmask])
6.    Optimization methods for last-mile logistics problems
Contact: Jenny Fajardo ([log in to unmask])
7.    Artificial Intelligence methods for next generation transport 
management
Contact: Antonio D. Masegosa ([log in to unmask])
8.    End-to-end design of optimization methods through differential 
programming
Contact: Antonio D. Masegosa ([log in to unmask])
9.    Evolutionary generative machine learning
Contact: Arka Ghosh ([log in to unmask])
10.    Addressing Class Imbalance in Automatic Machine Learning 
Paradigm: An Generative & Meta-Learning Approach
Contact: Arka Ghosh ([log in to unmask])

*Requirements*

Candidates should have a first class or good 2.1 honours degree in 
Software Engineering, Computer Engineering, Telecommunications 
Engineering or Transport Engineering (other equivalent disciplines will 
be also considered). An appropriate degree at Masters Level will be 
mandatory in order to access to the PhD program (applicants finishing a 
Master’s degree along this academic year will also be considered). 
Proficiency in spoken and written English is desired; knowledge of 
Spanish is not a requirement. To be eligible, candidates must become a 
full-time worker at DeustoTech facilities. All qualified candidates will 
be considered.

*Closing date*

April 24th, 2022 (applications will be evaluated in order of arrival). 
The selected applicants will go through a second phase, for choosing the 
final candidate. This second phase has a deadline May 6th.

*Further details*

Applicants must complete the following form with their e-mail, name, 
research topic preferences and CV in order to formalise their 
application and be evaluated.
Form: https://forms.gle/iZjoboGUh7D7BbBR6

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