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IK4 Doctorados

 

CEIT

Multicultural center which develops applied research programs to improve the innovative capacity of companies.

 
DOCTORAL OFFERS

CEIT

 

Microwave and millimeter-wave materials characterisation

CEIT

START: 09/2016

OPEN

The objective of the thesis will be to develop non-destructive techniques for characterising materials with microwaves. As part of a multidisciplinary and varied work group, the doctoral candidate will study the iteration of different materials using microwaves, propose novel monitoring systems, design and implement those systems at prototype level and test them. The end goal of the group will be to develop these prototypes up to the product phase in response to specific industrial needs.

OBTAINING DOCTOR DEGREE: 10/2019


Information and Communication Technologies

Sensors and Analogue Electronics

 

Application of advanced signal processing techniques for estimation of material properties

CEIT

START: 09/2016

OPEN
Estimating the properties of a workpiece’s materials based on the effect that the properties produce in the signal changes that are applied to the workpiece is the basis of many techniques used in non-destructive testing.The objective of the thesis is to study the benefits that can be obtained from the analysis and detection capability of theparameters of the workpiece under study by applying advanced signal processing techniques to the signal directly and to develop ad-hoc

OBTAINING DOCTOR DEGREE: 10/2019


Information and Communication Technologies

Electrónica Digital y Comunicaciones

 

Big data technologies in advanced predictive systems.

CEIT

START: 09/2016

OPEN

New technologies continue to allow us to collect and process more and more data that is heterogeneous in nature and geographically dispersed. By using these data and applying modelling, data mining and machine learning techniques, the project will respond to issues in predictive maintenance through innovative solutions.

OBTAINING DOCTOR DEGREE: 10/2019


Information and Communication Technologies

Data Analysis and Information Management

 

Supervised and unsupervised learning techniques for detecting technical losses (leaks) and non-technical losses (fraud) and water consumption forecasting for water delivery systems

CEIT

START: 09/2016

OPEN
The sustainable and integrated management of water resources is one of the most complicated global issues for drinking water distributors. Fresh water is a limited and valuable resources, and it must be preserved and used accordingly. Given the fact that water is a scarce resource and the other issues that have arisen due to population growth and the effects of climate change, water must be managed in an efficient manner, where the primary goal is ensuring that the maximum amount of...

OBTAINING DOCTOR DEGREE: 10/2019


Water and Health

Big data, Data analytics and machine learning

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