environmental science jobber

10th August 2025

The Faculty of Technology, Natural Sciences and Maritime Sciences (TNM) has a vacancy for a 100 % position as PhD Research Fellow in Transformative AI for Railway Systems (TransAIRail) from August 18, 2025.

The position is located at the Department of Electrical Engineering, Information Technology, and Cybernetics and reports to the Head of Department. The position will be part of the research group, “Electrical Power Systems” (EPS). The location of employment is Porsgrunn.

The employment period will be three years full time, and there is a premise for employment that the PhD Research Fellow is enrolled in USN’s PhD-program in PhD in Technology within three months of accession in the position. It may be possible to get a four-year full-time period consisting of 75 % PhD Research Fellow and 25 % teaching duties.

“Transformative AI for Railway Systems” (TransAIRail) project combines Power Engineering and Artificial Intelligence (AI) for developing more reliable systems for Railway Transportation and contributes to Green Transportation. The goal is to identify early signs of wear or faults of the railway power system to improve maintenance planning and make such systems more reliable. BaneNOR are responsible for the Norwegian rail infrastructure and oversees operations, maintenance and construction of railways throughout the country. This includes 4200 kilometres of tracks, 335 stations and stops and more than 4300 properties.

BaneNOR wants to reduce maintenance costs and increase reliability of their converter stations. Voltage is being transformed from 22 to 132 kV feeding voltage transformed to 16 kV, and frequency is transformed from 50 to 16 2/3 Hertz. Bane NOR collects real time data from their converters, with a high granularity. As per today BaneNOR has a scheduled maintenance program. To reduce costs, they want to introduce non-invasive predictive analysis.

Predictive maintenance and condition monitoring is a hot topic in electric power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods to predict the probability of fault occurring. Most companies have this as a priority task, to meet the targets formulated in UN’s Sustainable Development Goals.

This project supports USN’s strategic research areas within Energy, Climate and Environment and Regional Growth, and integrates the researchers from the Electrical Power Systems (EPS) research group (RG) and Applied Modeling and Control (AMOC) RG. Power Engineering and AI are important competence areas for USN. The project's subject area is within the master's programs EPE (Electrical Power Engineering) and ITA (IT and Automation), and partly within Computer Science.

The proposed project aims to evaluate solutions that can support the future operation of the railway system. In particular, the student may focus on the following research goals:

• Is it possible to build robust models based on the existing data?
• Is the collected data sufficient, or is it a need to collect more data? In that case, what type of data is needed?
• How to deal with Time Series Data for developing these AI/ML models?
• What is the feasibility of implementing these AI/ML models in BaneNORs existing systems?
• Any kind of modifications must be done to successfully implement AI/ML in BaneNORs existing systems?

The project aims to strengthen the overall digital competence at USN in collaboration with BaneNOR.

Eligibility Requirements:

• Master’s degree in Electrical Power Engineering or Computer Science with focus on AI, equivalent to a Norwegian master’s degree.
• Documented proficiency in English (Nordic applicants may submit their high school diploma as proof).
• Ability to collaborate and work effectively in an international and interdisciplinary research environment.
• Applicants with a strong background in STEM fields (e.g., Electrical power engineering, control system engineering, Physics or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning).
• The Master’s thesis must be included in the application.

Ideal Candidate:

• Demonstrates experience or strong interest in modelling, programming, systems thinking, and qualitative/quantitative research methods.
• Documented programming experience for example GitHub project on MATLAB, Python, Julia, Javascript, DigiSilent Power Factory.
• Possesses a strong academic record, with relevant experience in either industry or academia, and can show experience from paper publishing.
• Has prior professional experience and a solid understanding of workplace responsibilities and expectations, which will be considered a key advantage.
• Shows a deep interest in interdisciplinary research, is capable of independent work, and actively engages with the supervision team to foster collaborative research.

For admission to the Phd Program the weighted average grade is B or higher is usually required. The applicant must have gained the degree within the start date of the position, so applicants in the last semester of their master’s degree are also encouraged to apply. The candidate must meet the requirements for admission to the faculty's Doctoral Program in Technology

The candidate must have the ability to work independently and at the same time have the motivation to share knowledge and take part in teamwork. Co-operation between staff members is an integrated part of the working atmosphere at the University of South-Eastern Norway. The candidate must be motivated and demonstrate a proven ability to work effectively within a team and in a collegiate manner to formulate and realize common objectives. Personal suitability for the post will be emphasized.

Documentation of skills in English language:

Strong communication skills in English language skills are required for participation in the doctoral program. International applicants must document this with a valid certificate from one of the following tests:

• TOEFL – Test of English as a Foreign Language, Internet-Based Test (IBT). Minimum result: 90
• IELTS – International English Language Testing Service. Minimum result: 6.5
• Certificate in Advanced English (CAE) eller Certificate of Proficiency in English (CPE) from Cambridge University
• PTE Academic – Pearson Test of English Academic. Minimum result: 62

The following applicants are exempt from the above requirements:

• applicants with one year of completed university studies in Australia, Canada, Ireland, New Zealand, the United Kingdom, the United States
• applicants with a completed master's degree with English as the language of instruction in an EU/EEA country

The candidate may have to apply for a Norwegian security[BW1] clearance during the project period.

• Strongly motivated and ambitious.
• Be structured, targeted and solution oriented.
• Have motivation to work interdisciplinary.
• The successful candidate should be creative and actively contribute to the team he/she will be part of.
• Have good dissemination skills.
• Personal skills like a positive and friendly attitude, and contributing to a sustainable social environment will also be valued.

• A stimulating and growing research environment, with good opportunities to develop your career and your academic skills.
• A good social environment.
• An open and inclusive work environment with dedicated colleagues.
• Attractive welfare benefits in the State Pension Plan.
• Opportunity for physical activities within working hours

PhD Research Fellow (code 1017): NOK 550 800,- a year. Further promotion will be based on time served in the position.

A statutory contribution to the state pension plan will be deducted from the employee’s salary.

The Academic Appointments Board for PhD Research Fellowships is responsible for the appointment. An expert assessment of applicants will be carried out. The candidates deemed best qualified will be invited to an interview.

The person appointed must comply with the laws, regulations and agreements that apply at any given time to the post. Please note that approved work permit is a prerequisite for the employment.

According to its human resources policy, the University of South-Eastern Norway targets a balanced gender composition and aims to recruit persons with a background as an immigrant.

The Department has few women appointed in scientific positions, and women are therefore particularly encouraged to apply.

The University contributes to the Inkluderingsdugnaden (a voluntary scheme to promote inclusion), and it is our aim that our employees, to the fullest extent possible, shall reflect the diversity of the general population. We therefore encourage qualified applicants with disabilities to apply for the post. The University will facilitate the workplace for employees with disabilities.

Pursuant to section 25, 2nd paragraph of the Freedom of Information Act, information on the applicant may be disclosed even if the applicant has requested not be included on the list of applicants. Applicants will be notified if such requests are not allowed.

For more information about the position, please contact:

Main supervisor Assoc. Prof. Nils Jakob Johannesen (nils.j.johannesen@usn.no) +47 35 57 51 55 at the Faculty of Technology, Natural Sciences and Maritime Sciences, Department of Electrical Engineering, Information Technology and Cybernetics.

For questions regarding the recruitment process, please contact:

HR Advisor: Ruth Helen Haugerud, ruth.haugerud@usn.no (+47 35 95 26 17)

The University of South-Eastern Norway makes use of online application management. Applicants to the post must register their application and CV with enclosures online via the Jobbnorge recruitment portal by clicking on the link on the right-hand side – “” (Apply for the post).

The following documents shall be attached to the online application:

• Cover letter outlining the motivation and a detailed Curriculum Vitae (CV).
• Transcripts and diplomas of Bachelor's and Master's Degrees.
• The transcript should clearly show the grades obtained for different courses taken at the Bachelor and Master Degree.
• A 5-page maximum project description. The candidate should describe how he/she would carry out the tasks if he/she is offered this position. The description preferably also contain new ideas or methods that the candidate would think of using them for the execution of this PhD project.
• A copy of master thesis and any scientific publications and a list of these; GitHub profile with project is also relevant.
• Three references (contact information).
• Other relevant certificates (if applicable, must be specified).

Please note that all documents must be in a Scandinavian language or in English. Any translations must be certified.

If your higher education is from a university outside of Norway, we require it to be recognized by the Norwegian Directorate of Higher Education and Skills. You must apply for the recognition before the application deadline for this position expires. Add a receipt on your application or recognition when applying. The recognition must be sent to us and is a requirement for being hired.

The research area for the position may include technologies referred to in the Ministry's export control regulations. Relevant license or security clearances may therefore be required.

The application will be assessed on the basis of the attached documentation as requested above. Each applicant is responsible for ensuring that the required documentation has been uploaded with the application deadline.

The University has been awarded a Charter & Code certificate by the European Commission, and is entitled to use the HR Excellence in Research (HRS4R) logo. The University is also a member of the EURAXESS network, which contributes to good working conditions for mobile researchers.

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At USN you’ll contribute to a mission that matters. The University of Southeastern Norway was established in 2018, following the merger of several smaller university colleges, some with historical roots dating back to the 17th and 18th centuries. We are committed to collaborative problem-solving, aiming to provide solutions that benefit our communities – locally as well as globally.

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