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Responsible consumption for all

The candidate will join an IIT work team to participate in a three-year project. The main objective of the project is to improve the consumption habits and build a culture of responsible electricity consumption in society. The aim is to develop a system based on machine learning techniques that, based on data related to customer's consumption habits, is able of making personalized recommendations to improve the efficiency of their consumption. For this, there will be a sample of customer data in which the consumption of their devices at home will be monitored. The project is carried out in close collaboration with a multidisciplinary team from Endesa, funded by the Ministry of Science and Innovation, within the State Program for Research, Development and Innovation oriented to the challenges of society.

It offers
Annual full-time contract for the development of projects. Besides, the Research Assistant could take training activities. This modality allows the Research Assistant to establish a very close professional relationship with the companies with which he/she collaborates, thus nourishing his/her research with the experience accumulated during the projects. Although this modality does not necessarily require enrolling in any program, the Research Assistant can apply for a PhD after the first two years. The Research Assistant is hired each year for a maximum period of 6. If he or she is not enrolled in a PhD program the contract cannot exceed two years. The gross salary of the first year is € 24.410 for 2020. In addition, the IIT covers 90% of the cost of training activities and the Research Assistant will have access to all the services offered by the University (Sports, Cultural Activities, Library, etc.).

The candidate must have a master's degree in engineering, physics or mathematics, being especially valuable the knowledge in programing, statistics and machine learning. Having a good academic report, as well as the candidate’s knowledge on these topics will also be considered in the assessment of candidate merits. Perfect spoken and written Spanish and excellent spoken and written English.

Curriculum vitae, academic record, cover letter and two recommendation letters.

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Academic Data
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