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Marie Curie Doctoral Candidates Vacancy Offers

 

1. Job Information

Organisation/Company: UNIZAR

Research Field: Engineering, Wind Energy, Data Science

Researcher Profile: First Stage Researcher (R1)

Country: Spain

Application Deadline: November 30

Type of contract: Temporary (3 years)

Job Status: Full Time

Offer Starting Date (Vacancy Opening): November 1

Is the job funded through the EU Research Framework Programme?: YES

Marie Curie Grant Agreement Number: 101168673

Is the Job related to staff position within a Research Infrastructure?: NO

 

2. Offer description

TWEED Project

TWEED is looking for 12 talented and motivated Doctoral Candidates (DCs) with the skills, knowledge and enthusiasm to work as part of a network to advance the field of digitalistion within the wind energy sector.

The “Training Wind Energy Experts on Digitalisation (TWEED)” Doctoral Network (DN) aims to train the next generation of excellent researchers equipped with a full set of technical and complementary skills to develop high-impact careers in wind energy digitalisation.

Co-funded by the European Commission through the Horizon Europe Marie Sklodowska Curie Doctoral Networks Programme, the TWEED network offers 12 Doctoral Candidates (DCs) positions to provide high-level training in the new emerging research field of Wind Energy Data Science and Digitalisation.

An outstanding research-for-innovation programme, and a unique training programme that combines hands-on research training, interactive schools and hackathons, innovation management and placements with industry partner organisations has been designed for the DCs who will participate in the network. Alongside the exciting research topics related to wind energy data science, the research programme also includes state-of-the-art technology to develop a new Wind Energy Data Science Hub that will facilitate a virtual research environment to foster collaboration, data sharing and testing of innovative solutions to significantly increase the value of wind energy.

The network will provide an interdisciplinary and inter-sectoral context to foster creativity in tackling wind energy data science and digitalisation challenges by developing solutions for commercial exploitation.

DCs will be trained in business innovation to extend their focus beyond the academic context, to be able to identify added-value products or services with the guidance from established researchers and entrepreneurs. As a result, a research-for-innovation mindset will be developed to provide enhanced career prospects for the fellows, equipping them with a complete set of thematic, technological and innovation skills.

DCs are expected to i) conduct high quality, original academic research in the fields of Wind Energy, Digitalisation, Data Science and Computer Science, ii) participate in the network’s planned training-dissemination activities and mobility plan, iii) collaborate with fellow researchers, with the goal of advancing and promoting the network's objectives.

The most talented and motivated candidates will be selected to participate in the network's interdisciplinary collaborative research training, preferably starting in February 2024. The assessment shall be carried out by the TWEED recruitment team.

 

Two DC positions are available at UNIZAR within the TWEED project:

Internal code of the position: DC5

Host Institution: Institute ENERGAIA, UNIZAR

Brief description of the project: European harmonisation of electricity markets is advancing for Day-Ahead Markets, but it is still far from being achieved in the case of Balancing Markets. Therefore, one of the first steps of this project will be to analyse the different European markets and their opportunities for the participation of wind power producers. The main objective is to develop a framework that proposes combined strategies for the day-ahead and balancing markets bidding of a wind farm or a fleet analysing aggregation approaches of farms dispersed spatially and with different turbine technologies. This project will combine all the available data from wind farms and markets with machine learning and probabilistic techniques considering turbine control features, wind power, and market price forecasting to maximise benefits and reduce risks. The fellow will be trained on the use of machine learning techniques in order to obtain and develop research and industrial results. Research results will include the analysis of European markets, especially balancing markets and provision of the different types of reserve (frequency- controlled reserve, automatic-activated frequency restoration reserve and/or manually activated frequency restoration reserve) by wind power plants depending on their control capabilities. As an industrial result, the developed framework will help in decision taking to provide coordinated strategies covering day-ahead and balancing market offers.

Secondments: Two secondment periods (3 months) are foreseen for working on the benefits of smart farm control for participating in secondary and day-ahead market offers at TUM (M24-M26) and to test results in real situations at CETASA (Spain) (M35-M37).

Personal Supervisory Team: Main Supervisor: Prof M. Paz Comech (co-supervisor Julio J. Melero) at Unizar, Prof. Carlo L. Bottasso at Tum and Javier Gracia at CETASA.

 

Internal code of the position: DC8

Host Institution: Institute ENERGAIA, UNIZAR

Brief description of the project: Wind farm operators can profit substantially from shifting towards predictive maintenance strategies rather than employing corrective tasks using SCADA-based condition monitoring systems (CMS). Nevertheless, the black-box character found in the market inhibits the generalised use of these systems. This project will combine all the available data from a wind turbine, alarms, low and high- frequency SCADA and maintenance reports, with explainable machine learning and probabilistic techniques to develop a prognosis tool for the preventive maintenance of the turbine. Unsupervised learning using classification methods will first allow the identification of important features in the datasets. Importance Ranking and Principal Component Analysis will help to reduce the feature space dimensionality providing a selected set of features. Finally, supervised classification and regression techniques, will be applied to the selected set of features to obtain prognosis models of failures including uncertainties. The models will be grouped in a practical tool /app capable of anticipating component failures in the turbine (with an explainable method), including the uncertainty, which will help indecision making for when to repair a component. The fellow will be trained on the use of the different covered machine learning techniques to obtain and develop research and industrial results. Research results will be obtained at three different levels: first, unsupervised ML will provide a set of features of the Wind Turbine SCADA data to be considered; second, the features dataset will be reduced by selecting the most appropriate methods; third, supervised ML methods will generate models for the prediction of failures. As the industrial result, the prognosis tool (concept) will be developed from the obtained models and validated with real data and benchmarking tools.

Secondments: Two secondment periods (3 months) are foreseen to support collaboration on data driven ML predictive maintenance with TU-DELFT (M24-M26) and to test the final tool with ANNEA (M35-M37).

Personal Supervisory Team: Main Supervisor: Prof Julio J. Melero at Unizar, Prof. Simon Watson at TU-Delft and Dr. Maik Reder at ANNEA.

 

3. Requirements

Research Field: Engineering, Wind Energy, Data Science, Computer Science

Education Level: Master Degree or equivalent

Skills / Qualifications:

  • Applicants must be proficient in the English language.  

  • Master degree or equivalent obtained by the time they are appointed. Students currently in the final year of a Master’s degree are encouraged to apply but should note that if selected, they will be expected to start their PhD in the first quarter of 2025.

Specific requirements:

  • A master or equivalent degree in Engineering.

  • A strong background in wind energy; specific knowledge on the topic of the applied-for position is a plus.

  • Excellent programming skills.

  • Excellent writing and communication skills in English.

  • Ability to work in a multi-cultural team and independently.

The successful candidate must also fulfill the requirements for admission to a PhD program at the Doctoral School of the University of Zaragoza.

Languages: English

Level: Excellent

 

4. Additional Information

Benefits

You will work under a 36-month employment contract with the competitive conditions and salary adapted to the living costs in each host country, set by the MSCA Doctoral Networks (DN). The MSCA DN programme offers a highly competitive and attractive salary and working conditions. The successful candidates will receive a salary in accordance with the MSCA regulations for DCs, according to the national rules of the country with full social security benefits.

The successful candidate will receive a financial package plus an additional mobility and family allowance according to the rules for Doctoral Candidates (DCs) in an EU Marie Skłodowska-Curie Actions Doctoral Networks:

  • Living Allowance of €3250/month.

  • Mobility allowance of €600/month to be paid to all DCs recruited.

  • Family allowance of €660/month to be paid depending on DCs family status

The gross salary will be calculated by deducting the applicable employer taxes and social security contribution for each country, from the amounts mentioned above and will be aproximately € 2700/month for a single person and € 3100/month for person with a child. Additional deductions may apply based on your personal circumstances and local tax/social security regulations.

In support of families with young children, flexible working hours will be offered to the DC whenever it is feasible within the requirements of the project.

Following the EU’s commitment to DEI, the TWEED network and the University of Zaragoza encourages and promotes the participation of under-represented groups such as women in technical careers, people from diverse economic and ethnic backgrounds, people with disabilities, those who identify as neurodivergent and LGBTQA+. The University of Zaragoza community aims to exercise a policy of equal opportunities at all times.

Additional information can be found in Information Note for Marie Sklodowska-Curie fellows in Doctoral Networks.

Eligibility criteria

All applicants must, at the date of the recruitment, comply with the following ELIGIBILITY CRITERIA:

  • Candidate status: At the time of recruitment, applicants must not hold a doctoral degree or equivalent.

  • Mobility Rule: Applicants can be of any nationality. However, applicants must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting organisation for more than 12 months in the 3 years immediately before the appointment. This excludes short stays such as holidays or compulsory national service

Candidates are required to document in their applications their compliance with the eligibility criteria. To prove their eligibility, candidates can use supporting documents such as studies, residense or work certificates.

 

5. Selection Process

Selection process complies with the guidelines set forth in the European Charter for Researchers, including the Code of Conduct for Recruitment of Researchers.

Candidates will be requested to provide their consent for their application documents to be shared among the members of the recruitment team for review (including other institutions than the institution to which they originally addressed their application). Additionally, they will be requested to consent (or decline) to having their application forwarded to another host institution within the network, should their profile be better suited for a different position. Personal documents and information of the candidate will be treated confidentially.

Eligibility check

  • The Recruitment Team of TWEED will gather the information from all candidates and will check that they comply with the eligibility criteria and that the applications are complete, in English, and submitted before the deadline.

  • The initial check of the eligibility criteria will have to be formally approved by the host institution at the time of recruitment of the appointed candidates.

  • Ineligible candidates will be notified via email.

Assessment:

A Selection Committee will be set up at the host institution, led by the Main Supervisor. The Selection Committee will assess all candidates according to their academic profile, personal motivation, relevant background, professional experience, scientific knowledge, transversal skills, soft skills and English proficiency. The Selection Committee will short-list at least the best 3 candidates.

Interview

The Selection Commitee will interview the short-listed candidates and will produce a ranked list of candidates that qualify for the position.

Decision

According to the procedure established in TWEED, the Selection Committee will submit its list of preferences to the Supervisory Board (the project's governing body). The SB will prepare the final ranking of candidates for each position.

Communications

Candidates will be informed of the status of their application during the selection process.

 

6. How to apply

The application must include:

  • Detailed CV:

    • Candidate personal information

    • Information about graduate and postgraduate degree and qualifications

    • Work experience

    • English proficiency

  • Eligibility information, countries of residence for the last 3 years

  • Motivation letter

  • The names and contact information of two referees.

  • Written agreement of the permission to share information with the TWEED project Recruitment Team.

  • Identification of other possible positions at TWEED in which you may be interested or which have also been applied for.

The application should be sent by email to tweedproject@unizar.es.

 

Work location

Number of offers available: 2

Company/Institute: Instute ENERGAIA, University of Zaragoza

Country: Spain

City: Zaragoza

Postal Code: 50018

Street: Mariano Esquillor 15

About

University of Zaragoza

The University of Zaragoza is a public teaching and research institution whose aim is to serve society. As the largest higher education centre in the Ebro Valley, the University combines almost fi ve centuries of tradition and history (since 1542) with a constantly updated range of courses. Its main mission is to generate and convey knowledge to provide students with a broad education. The University bases its principles on quality, solidarity and openness and aims to be an instrument of social transformation to drive economic and cultural development.

Research, technological development and constant innovation are essential for economic and social growth. Our research activity is channelled through the 222 research groups. At the University of Zaragoza, 288 researchers work in 170 research groups. University research institutes also provide doctoral, specialisation and postgraduate programmes based on their specialities. They are primarily interdisciplinary in structure and activity. The University of Zaragoza has five own university institutes, four joint institutes and one affiliated institute. Challenge. Change. Impact!

Instituto Universitario de Investigación Mixto ENERGAIA

The Joint Research Institute in Energy and Resources Efficiency of Aragón (ENERGAIA) was created in 2009 with the former name of CIRCE, as a joint collaboration between the Universitiy of Zaragoza and the CIRCE Foundation. Its headquarters are in the CIRCE Building, on the Ebro River Campus of the University of Zaragoza.

Its main objective is to promote research of excellence and quality and technology transfer, promoting an energy scenario based on Renewable Energies, Resource Efficiency and Sustainability, which responds to the needs of society.

The ENERGAIA Institute aims to be a centre of reference in Renewable Energies, Resource Efficiency and Sustainability at regional, national and international level, capable of providing society with knowledge (research), technologies (transfer and dissemination) and people prepared to improve it (training). As a basis for such a claim, thousands of students from all continents have passed through the ENERGAIA Institute carrying out hundreds of doctoral theses, research articles and European, national, regional and business projects.

Click here to go to the website of the ENERGAIA Institute.

 

7. Contact

For more information about this positions, please contact Prof. M. Paz Comech (DC5) e-mail: mcomech@unizar.es and Prof. Julio J. Melero (DC9) e-mail: melero@unizar.es

Main contact of the TWEED project: tweedproject@unizar.es