4+4 PhD positions in Energy and Artificial Intelligence

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SDU Center for Energy Informatics invites applications for a number of 4+4 PhD positions. The starting date for the positions is September 1, 2022. Application deadline is June 30, 2022. 

SDU Center for Energy Informatics (CEI) is an interdisciplinary industry-oriented research and innovation center with an international outlook. The center focuses on development of innovative digital energy solutions that can facilitate the transition towards a sustainable energy system. The center is part of the Faculty of Engineering (TEK), University of Southern Denmark, and located at the main Campus in Odense, Denmark. 

Profile and requirements
To apply for the 4+4 PhD positions, it is required that the applicant is enrolled in one of the Faculty of Engineering master’s programmes in Energy Systems Engineering or Software Engineering plus has completed the first year at the time for enrollment.

We are looking for highly motivated and ambitious students with excellent knowledge of English (written and spoken), who can work well in a team as well as independently and quickly acquire knowledge in new topics. 

About the PhD positions
The PhD positions are offered within the following research topics.

Topic 1. Multi-dimensional assessment of resiliency and sustainability sector coupling solutions

This research topic aims to develop an AI-based forecasting and multi-criteria evaluation framework for assessing the resiliency and sustainability of sector coupling designs and strategies. The framework will provide stakeholders in the energy ecosystem with foresight on the future consequences of alternative designs and strategies for sector coupling solutions. The research will be conducted in collaboration with national and international companies and organizations representing stakeholders in the energy ecosystem.

Topic 2: Identification, classification and prediction of driver behavior for optimal fuel consumption

The aim of this research topic is to develop and implement AI-based methods for identifying, classifying, and predicting optimal driver behavior for reducing fuel consumption in the transportation sector. The developed methods will be used in a real-time Advisory system for coaching drivers to avoid excessive fuel consumption. The research is conducted in collaboration with leading companies and organizations in the Danish transportation sector.

Topic 3: Identification and classification of process operation patterns for optimal energy consumption and product quality

The focus of this research topic is to develop a data-driven AI framework for identifying and classifying best-practice patterns for energy-efficient operation of industrial processes. The framework will provide companies in the manufacturing and process industry with actionable insights on the energy use of their daily operations and enable them to take actions to reduce their CO2e emissions. The research is conducted in collaboration with leading companies in the Danish IT and industrial sectors.

Topic 4: Open data spaces for provision of AI-based smart city services

This research topic focus on the development and deployment of enabling technologies for creation of open data spaces that can facilitate the innovation of AI-based smart city services. The research will provide companies with insight and best-practice for establishing their data and AI development workflows. The research is conducted in collaboration with leading global providers of open-source platforms and the European ERA-Net Smart Energy Systems community on digital transformation for green energy transition.

Topic 5: Smart asset maintenance and management for electric power distribution grids

The purpose of this research topic is to develop a machine learning-based prescriptive maintenance and asset management tool that enables distribution system operators to reduce their asset maintenance and management costs. The developed tool will provide DSOs with actionable insight about their grid assets before faults are expected to occur. The research is conducted in collaboration with Danish DSOs and leading companies in the energy sector.

Topic 6: Digital Twins for buildings energy performance optimization and intelligence quotient enhancement

The aim of this research topic is the design, development, and demonstration of an innovative digital twin platform to optimize buildings energy performance and enhance their intelligence quotient. The digital twin platform will improve best practice for building performance monitoring, commissioning, and operation management. The research is a collaboration between commercial and public partners.

Topic 7: A Digital Twin solution for optimal energy retrofit decision-making and decarbonization of buildings

The research is aiming to design, develop, and demonstrate a digital twin solution to serve for optimal energy retrofits decision-making, retro-commissioning and performance optimization of existing non-residential buildings. The digital twin solution will enable building owners and facility manager to make cost-optimal decision for building retrofits and operational management. The project is in collaboration between IT companies and building owners in the public sector.

In the motivation letter, the applicant has to state the number of the PhD research topic the applicant applies for. If the applicant wants to apply for more than one topic, the applicant has to provide a prioritized list.

Contact information
Further information is available by contacting Head of Centre, Professor Bo Nørregaard Jørgensen, bnj@mmmi.sdu.dk

If you experience technical problems you must contact support-sdujob@sdu.dk. 

Important information before applying
To be considered for the position it is required that the applicant is enrolled in a Master's programme (kandidatuddannelse) at the Faculty of Engineering, SDU, and has completed the first year at the time for enrollment.

The 4+4 PhD fellowship programme is divided into a 22 months grant period followed by an employment period. When the master's degree (kandidatuddannelse) is achieved and you as least have attained a grad of 10 (Danish scale), you will be employed at the same terms as a 3-year PhD fellowship. Read about Work and salary conditions. 

The enrollment and employment will cease without further notice at the end of the 4-year period. A PhD fellow is not allowed to have any kind of sideline employment, while enrolled as PhD fellow at the faculty.

Employment is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations.

The successful candidate will be enrolled at SDU in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order), read more here.

The assessment process
Read about the Assessment and selection process. Shortlisting may be used. 

Application procedure
The Faculty expects applicants to read the Faculty information for prospective PhD students and the SDU information on How to apply before applying.

The applications must include the following - the required forms must be found at the Faculty website:

  • Completed TEK PhD application form for 4+4 applicants. Find the form at the Faculty website.
  • Motivation letter - remember to state the number of the topic. Upload in the field called “Project description”.
  • Detailed Curriculum Vitae describing research, publication and teaching experience, computational skills and including personal contact information.
  • Verified copies of the official bachelor diploma and transcripts of exams plus master's transcripts of exams, both the original documents and in professional English translation.
  • Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website. Upload in one of the fields called “Publication”. 
  • An official document describing the grading scheme of the awarding universities (if not Danish). Upload in one of the fields called “Publication”. 
  • List of publications, in case you have any publications. 
  • References (names and emails) and reference letters may also be included. You're welcome to use the form for reference letter at the faculty website. 
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Skriv i din ansøgning, at du fandt jobbet på ofir.dk


4+4 PhD positions in Energy and Artificial Intelligence

SDU Center for Energy Informatics invites applications for a number of 4+4 PhD positions. The starting date for the positions is September 1, 2022. Application deadline is June 30, 2022. 

SDU Center for Energy Informatics (CEI) is an interdisciplinary industry-oriented research and innovation center with an international outlook. The center focuses on development of innovative digital energy solutions that can facilitate the transition towards a sustainable energy system. The center is part of the Faculty of Engineering (TEK), University of Southern Denmark, and located at the main Campus in Odense, Denmark. 

Profile and requirements
To apply for the 4+4 PhD positions, it is required that the applicant is enrolled in one of the Faculty of Engineering master’s programmes in Energy Systems Engineering or Software Engineering plus has completed the first year at the time for enrollment.

We are looking for highly motivated and ambitious students with excellent knowledge of English (written and spoken), who can work well in a team as well as independently and quickly acquire knowledge in new topics. 

About the PhD positions
The PhD positions are offered within the following research topics.

Topic 1. Multi-dimensional assessment of resiliency and sustainability sector coupling solutions

This research topic aims to develop an AI-based forecasting and multi-criteria evaluation framework for assessing the resiliency and sustainability of sector coupling designs and strategies. The framework will provide stakeholders in the energy ecosystem with foresight on the future consequences of alternative designs and strategies for sector coupling solutions. The research will be conducted in collaboration with national and international companies and organizations representing stakeholders in the energy ecosystem.

Topic 2: Identification, classification and prediction of driver behavior for optimal fuel consumption

The aim of this research topic is to develop and implement AI-based methods for identifying, classifying, and predicting optimal driver behavior for reducing fuel consumption in the transportation sector. The developed methods will be used in a real-time Advisory system for coaching drivers to avoid excessive fuel consumption. The research is conducted in collaboration with leading companies and organizations in the Danish transportation sector.

Topic 3: Identification and classification of process operation patterns for optimal energy consumption and product quality

The focus of this research topic is to develop a data-driven AI framework for identifying and classifying best-practice patterns for energy-efficient operation of industrial processes. The framework will provide companies in the manufacturing and process industry with actionable insights on the energy use of their daily operations and enable them to take actions to reduce their CO2e emissions. The research is conducted in collaboration with leading companies in the Danish IT and industrial sectors.

Topic 4: Open data spaces for provision of AI-based smart city services

This research topic focus on the development and deployment of enabling technologies for creation of open data spaces that can facilitate the innovation of AI-based smart city services. The research will provide companies with insight and best-practice for establishing their data and AI development workflows. The research is conducted in collaboration with leading global providers of open-source platforms and the European ERA-Net Smart Energy Systems community on digital transformation for green energy transition.

Topic 5: Smart asset maintenance and management for electric power distribution grids

The purpose of this research topic is to develop a machine learning-based prescriptive maintenance and asset management tool that enables distribution system operators to reduce their asset maintenance and management costs. The developed tool will provide DSOs with actionable insight about their grid assets before faults are expected to occur. The research is conducted in collaboration with Danish DSOs and leading companies in the energy sector.

Topic 6: Digital Twins for buildings energy performance optimization and intelligence quotient enhancement

The aim of this research topic is the design, development, and demonstration of an innovative digital twin platform to optimize buildings energy performance and enhance their intelligence quotient. The digital twin platform will improve best practice for building performance monitoring, commissioning, and operation management. The research is a collaboration between commercial and public partners.

Topic 7: A Digital Twin solution for optimal energy retrofit decision-making and decarbonization of buildings

The research is aiming to design, develop, and demonstrate a digital twin solution to serve for optimal energy retrofits decision-making, retro-commissioning and performance optimization of existing non-residential buildings. The digital twin solution will enable building owners and facility manager to make cost-optimal decision for building retrofits and operational management. The project is in collaboration between IT companies and building owners in the public sector.

In the motivation letter, the applicant has to state the number of the PhD research topic the applicant applies for. If the applicant wants to apply for more than one topic, the applicant has to provide a prioritized list.

Contact information
Further information is available by contacting Head of Centre, Professor Bo Nørregaard Jørgensen, bnj@mmmi.sdu.dk

If you experience technical problems you must contact support-sdujob@sdu.dk. 

Important information before applying
To be considered for the position it is required that the applicant is enrolled in a Master's programme (kandidatuddannelse) at the Faculty of Engineering, SDU, and has completed the first year at the time for enrollment.

The 4+4 PhD fellowship programme is divided into a 22 months grant period followed by an employment period. When the master's degree (kandidatuddannelse) is achieved and you as least have attained a grad of 10 (Danish scale), you will be employed at the same terms as a 3-year PhD fellowship. Read about Work and salary conditions. 

The enrollment and employment will cease without further notice at the end of the 4-year period. A PhD fellow is not allowed to have any kind of sideline employment, while enrolled as PhD fellow at the faculty.

Employment is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations.

The successful candidate will be enrolled at SDU in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order), read more here.

The assessment process
Read about the Assessment and selection process. Shortlisting may be used. 

Application procedure
The Faculty expects applicants to read the Faculty information for prospective PhD students and the SDU information on How to apply before applying.

The applications must include the following - the required forms must be found at the Faculty website:

  • Completed TEK PhD application form for 4+4 applicants. Find the form at the Faculty website.
  • Motivation letter - remember to state the number of the topic. Upload in the field called “Project description”.
  • Detailed Curriculum Vitae describing research, publication and teaching experience, computational skills and including personal contact information.
  • Verified copies of the official bachelor diploma and transcripts of exams plus master's transcripts of exams, both the original documents and in professional English translation.
  • Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website. Upload in one of the fields called “Publication”. 
  • An official document describing the grading scheme of the awarding universities (if not Danish). Upload in one of the fields called “Publication”. 
  • List of publications, in case you have any publications. 
  • References (names and emails) and reference letters may also be included. You're welcome to use the form for reference letter at the faculty website. 
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Skriv i din ansøgning, at du fandt jobbet på ofir.dk


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