Ledig stilling på Universitetet i Oslo

Blindern og Urbygningen (Foto: Wikimedia og Colourbox)
Blindern og Urbygningen (Foto: Wikimedia og Colourbox)

2 PhD Research Fellow positions in Intelligent Dynamic Energy Systems

Deadline: 29.03.2023

Universitetet i Oslo

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7500 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.

Universitetet I Oslo (UiO) utvider sin aktivitet ved Campus Kjeller for å styrke vår utdanning, forskning og innovasjon på teknologi for en bærekraftig fremtid. UiO er et høyt rangert universitet hvor Institutt for teknologisystemer (ITS) på Kjeller har fokus på anvendt forskning innenfor fagfeltene fornybar energi, autonome systemer, rom og sikkerhet.

Her på Kjeller er også Forsvarets forskningsinstitutt (FFI) og Institutt for energiteknikk (IFE) som ITS jobber tett sammen med. ITS sin forskning er tett og tverrfaglig koblet til de andre instituttene ved UiO på Blindern, med Oslo Science City, samt med andre internasjonale aktører.

ITS tilbyr flere masternivå-programmer, både alene og sammen med andre institutt. Våre program er Fornybare energisystemer, Kybernetikk og autonome systemer, Robotikk og intelligente systemer, og Informasjonssikkerhet. ITS er vert for SFI Centre for Space Systems and Sensors (CENSSS) som blant annet har operasjonen av georadaren Rimfax på NASA sin Perserverance rover på Mars. Et nytt masterprogram på romsystemer er også under planlegging.

På nåværende tidspunkt har instituttet 9 faste vitenskapelige ansatte, ca. 35 bistillinger fra Kjellermiljøet og industri og ca. 20 PhD stipendiater.

Denne stillingen er en del av utvidelsen av UiO sin aktivitet på Campus Kjeller. Campus Kjeller ligger 20km nordøst for Oslo, mellom Oslo sentrum og Oslo lufthavn, Gardermoen. Det tar 20 minutter med kollektivtransport fra Oslo sentrum til campus.

About the position

Two PhD Research Fellow positions are available at the Department of Technology Systems (ITS), University of Oslo, in the following areas:

●Numerical modeling of Dynamic Energy Systems

●Control of Intelligent Dynamic Energy Systems with Machine Learning

The purpose of the fellowships is research training leading to the successful completion of a PhD degree.

The fellowship period is 3 years.

A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

Starting date, as soon as possible.

Job description

The PhD research fellow will be part of the IDES (Intelligent Dynamic Energy Systems) project. IDES is a collaboration project between the Institute For Energy Technology (IFE), The Norwegian Defense Research Establishment (FFI) and Department of Technology Systems (ITS) at the University of Oslo, all located at Kjeller outside Oslo, Norway.

Energy systems can be complex with many components exhibiting highly dynamic behavior in terms of unpredictability in energy consumption and production. For example, variable renewable energy sources, such as solar power or wind power, are intermittent and can be hard to predict, so dealing with the dynamics in energy systems is a challenge that is expected to receive growing interest in the years to come.

The project will employ three PhD fellows in total:

  • One PhD fellow (PhD 1) will develop a generic numerical model for dynamic energy systems. The model will be a basic building block for design and control of the system, and it allows for numerical simulations of the system, based on the physical features and characteristics of the system.
  • The second PhD student (PhD 2) will focus on the control of dynamic energy systems. The challenges posed by the growing dynamics of energy systems call for adding improved intelligence to control the energy systems. The controller is added on top of the model of the system, and the forecasting is a vital input to this model.
  • In addition, there is a third PhD candidate (PhD 3) that is already employed, who will focus on developing methods for high performance short-term forecasting of energy supply and demand, since forecasting is crucial for these dynamic systems. The methods will employ AI approaches, and will need to combine information from several different data sources, such as sensors, weather data, consumption data etc.

All three PhD candidates will work mostly independently on their specific topic, but they will also be required to work as a team combining energy systems modeling, control and forecasting for specific scenarios.

As the PhD candidate 3 is already employed, only the PhD1 and PhD2 positions are vacant.

Work tasks:

The PhD research work will include the following topics and tasks:

PhD 1: Numerical modeling of Dynamic Energy Systems

  • Build knowledge about how to numerically model intelligent dynamic energy systems with goals and restrictions on multiple time scales and uncertainty regarding energy input, production and consumption
  • Develop a generic and computationally efficient numerical model that can be used to model a wide range of specific cases
  • Dissemination through scientific publications

PHD 2: Control of Intelligent Dynamic Energy Systems with Machine Learning

  • Build knowledge about artificial intelligence-based control of energy systems with short term uncertainty and multiple long and short-term goals and restrictions
  • Develop generic control system strategies based on artificial intelligence for dynamic energy systems with goals and restrictions on multiple time scales
  • Quantify effects of the newly developed techniques compared to conventional control strategies based on physics and control theory
  • Dissemination through scientific publications

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

Required qualifications

  • Master's degree or equivalent in a relevant field such as such as Computer Science, Machine Learning, Cybernetics, Autonomous Systems, Energy Systems, Robotics, Statistics, Physics, Mathematics or similar.
  • Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
  • The PhD candidate must have fluent oral and written communication skills in English.
  • The position's subject area may require licensing under the Norwegian Export Control Act. In order to be considered for the position, it is a prerequisite that UiO must be able to be granted such license. The PhD candidate must be eligible to obtain a security clearance according to the Norwegian National Security Act (Lov om Nasjonal Sikkerhet, a.k.a. “Sikkerhetsloven”), at a level that satisfies the research institute partners of the project, FFI and IFE.

Desired qualifications

The PhD candidate would preferably also have one or more of the following:

  • Good programming skills in languages, such as Python, C/C++, and/or similar
  • Education, training or experience with Machine Learning or Deep Learning algorithms (most relevant for PhD 2) or with system modeling and system modeling methods (most relevant for PhD 1)
  • A good publication track record
  • Work experience from the military sector or the energy sector

Grade requirements:

The norm is as follows:

  • The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
  • The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
  • The Master’s thesis must have the grade B or better in the Norwegian educational system
  • Fluent oral and written communication skills in English
  • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

Personal skills

  • Ability to take initiative and come up with new ideas to solve theoretical and practical problems
  • Ability to work independently as well as in a team
  • Good communication skills

We offer

  • Salary NOK 501 200 – 544 400 per year depending on qualifications as PhD Research Fellow (position code 1017)
  • Attractive welfare benefits and a generous pension agreement
  • Vibrant international academic environment
  • Career development programmes
  • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

  • Cover letter - statement of motivation and research interests
  • CV (summarizing education, positions and academic work - scientific publications)
  • Copies of the original Bachelor and Master’s degree diploma, transcripts of records and letters of recommendation
  • Documentation of English proficiency
  • List of publications and academic work that the applicant wishes to be considered by the evaluation committee
  • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
  • Please indicate in your application cover letter which positions you are applying for, PhD 1, PhD 2 or both, and which position you would prefer if you are applying for both.

The application with attachments must be delivered in our electronic recruiting system, please follow the link “Apply for this job”. Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English (or a Scandinavian language).

Interviews with the best qualified candidates will be arranged.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

For futher information about positions and recruitment process, please contact:

  • Paal E. Engelstad, Professor ITS, Mobile: +47- 41633776, email: [email protected]
  • Roy Stenbro, Department Head Wind Energy, IFE, Mobile: +47 92030992, email: [email protected]
  • Narada D. Warakagoda, Principal Research Scientist, FFI, Mobile: +47 48020811 email: [email protected]

For technical questions regarding the recruitment system JobbNorge, please contact:

Apply for this job

Powered by Labrador CMS