PhD Research Fellow in Educational Sciences

University of Oslo

About the position​ We invite applications for position as PhD Research Fellow in computer science/AI for energy informatics available at the Department of Informatics (IFI), UiO Starting date: as soon as possible, no later than Sept. 2026. The fellowship period is three years.  Depending on the candidate and the teaching needs of the department, the fel-lowship period can be extended either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up top four years. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Place of work is the Department of Informatics at Forskningsparken, Oslo. Job description​ Description about scope of the PhD research:​ Do you have a background in energy informatics, computer science, or energy systems, and are you are interested in edge intelligence, multi-agent AI, and interdisciplinary collaborative research, and looking for a PhD position, this opportunity can be for you. The Energy Informatics EI@ND Networks and Distributed Systems group at the Department of Informatics (IFI), University of Oslo (UiO) is seeking a highly motivated PhD candidate for a fully funded full time PhD position for the Norwegian National AI Center on AI for Decisions (aiD). The fellowship is for research training for a period of 3 years leading to the successful completion of a PhD degree. As a PhD candidate with us, you will gain valuable experience opening up exciting career opportunities in academia and industry. About the Project:​ The position will be part of AID, the Norwegian Centre on AI for Decisions, an interdisciplinary national AI centre in Norway led by NTNU and SINTEF. AID brings together academic institutions, research organizations, and more than 50 professional organizations. Its primary objective is to advance AI for decision-making through fundamental research and real-world use cases, ensuring that AI-enhanced human decisions and autonomous systems are effective, safe, and trustworthy in sectors critical to society. The global energy system is undergoing a profound transformation driven by the rapid uptake of distributed renewable energy resources and the envisioned empowerment of prosumers. Thus, the traditional centralized grid is evolving into a highly distributed, data/ computation-intensive, AI-driven ecosystem in which smart meters, microgrids, aggregators, and edge devices actively participate in energy production, storage, consumption, and market interactions. This transition is fundamentally reshaping the structure of energy networks, shifting from centralized control to distributed, prosumer-driven ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has its own objective (e.g, cost, profit, comfort, sustainability, etc.) and interacts with other agents for shared resources (e.g., grid capacity, energy prices). In this new paradigm therefore, multiple autonomous agents including households, aggregators, and grid operators-must make real-time, interdependent decisions under shared constraints and competing objectives. Multi-agent learning and optimization show promise in this regard. Yet, the deployment of AI for decision making in critical infrastructure like the energy sector introduces challenges related to safety, fairness, accountability, transparency, and explainability (FATE), as well as compliance with emerging regulatory frameworks such as the EU AI Act and Data Act. More About the Position:​ In this project, you will develop game-theoretic AI frameworks by integrating Data-driven intelligence with principled decision structure for multi-agent decision making in energy systems. In addition, you will derive formal FATE metrics for the energy system and develop Explainable AI solutions to ensure transparency while also addressing privacy preservation and computation-efficiency requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and renewable integration) and (energy edge+) distribution grid resilience. Duties of the position:​ • Carry out research of high quality within the scope and framework described above • Actively Participate in activities of the Energy Informatics/ND research group • Complete academic training consisting of coursework corresponding to a minimum 30 ECTS • Produce publications of exceptional quality in relevant conferences, journals and actively contribute in popular science dissemination • Participate in international activities such as conferences and/or research stays in foreign educational institutions  What skills are important in this role?​ 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 (120 credits equivalent of the Norwegian Master’s degree program) in Electrical Engineering, Communication Engineering, Computer Science or other relevant discipline, with a Master Thesis in the Master’s degree program. • Foreign completed degree (M.Sc.level) corresponding to a minimum of four years in the Norwegian educational system • Must have documented solid mathematical foundations on optimization (e.g., optimization modelling and numerical optimization), game theory, AI/ML (A focus on explainable AI e.g., will be valuable) • Must have documented Background/Knowledge on Energy/Systems/Energy Informatics and edge intelligence etc. • Must have documented significant Knowledge/Research Background, or Must be able to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. • Must have very good programming competence in Python, Java, C/C++ or equivalent • Fluent oral and written communication skills in English Desired qualifications:​ • Publications in reputed journals and conferences in the field • Excellent presentation skills • Experience working in an cross-disciplinary/International Team Language requirement:​ • Good oral and written communication skills in English • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 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 For more information see: The purpose of the fellowship is research training leading to the successful completion of a PhD degree.  All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation. What are we looking for in you?​ Personal skills:​ • Ability to work both independently and as part of a team • Ability to work precise in a structured manner and swiftly adapts to new tasks • Good communication and collaboration skills • Positive attitude and the ability to handle hectic periods The candidate should demonstrate: • strong motivation, curiosity, proactiveness and a learning-oriented mindset • capability to work independently, take initiative, and maintain good structure and discipline in their work • communicate effectively and collaborate well with supervisors and peers • resilience and work constructively when facing challenges or setbacks • integrity and a strong sense of responsibility in their research conduct • high interest and motivation for collaboration with industrial and interdisciplinary teams • ability to write in a structured, clear and concise manner The evaluation considers many aspects of excellence, as well as the personal drive and organizational skills. The candidate should also possess good interpersonal and communication skills and show high level of motivation to work as part of an international team. Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications. We can offer you​ • A pleasant and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund  We need different perspectives in our work​ UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here.  We hope you will apply for the position with us. 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 and transcripts of records • Three letters of recommendation • Names and contact details of three references (name, relation to candidate, e-mail and telephone number) • Documentation of English proficiency if applicable • List of publications and academic work that the applicant wishes to be considered by the evaluation committee Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system. When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information​ The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.   The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.

University of Oslo

About the position​ We invite applications for a PhD Research Fellow position in Computational Nuclear Physics and Reactor Simulations is available at Department of Physics. The PhD Research Fellow will be part of the Norwegian Nuclear Research Centre (NNRC).  NNRC is a cross-disciplinary collaboration between Norway’s leading institutions within nuclear physics and nuclear chemistry research: University of Oslo (UiO), Norwegian University of Life Sciences (NMBU), and Institute for Energy Technology (IFE). The Centre addresses major research questions within the nuclear field spanning topics from nuclear properties and medical isotope production to reactor simulations and environmental radiochemistry. Starting date as soon as possible, preferably before December 1st, 2026. The fellowship period is three years. A fourth year maybe considered and it will involve 25 percent of other career-promoting work. Other career-promoting work may consist of teaching, supervision, 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.  Project description/work tasks​ The Nuclear Physics group at UiO is involved in several research themes within the Norwegian Nuclear Research Centre (NNRC), from fundamental research within nuclear properties and nuclear fission, to more applied research within nuclear simulations and radionuclide production and speciation. This PhD Research Fellow will mostly contribute to nuclear simulations (reactor simulations). The project will include reactor simulations of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate through system safety analysis of nuclear installations, using tools such as open simulations platforms. This research will be part of a larger international collaboration and be a part of the Norwegian Nuclear Research Centre. The candidate is expected to contribute to and partake in activities organised by the Centre. What skills are important in this role?​ 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 physics or nuclear technology, with specialization in nuclear physics or reactor physics • Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system • A solid background in scientific computing, for example Python Candidates without a master’s degree have until 1 October 2026 ​to complete the final exam. Desired qualifications:​ The following qualifications are considered strongly desirable and will be used in the ranking of the candidates: • Experience with reactor simulations in for example OpenMC or system codes, like RE-LAP • Experience with data analysis techniques  • Experience using ML • Familiarity with data analysis tools such as ROOT • Knowledge of reactor physics and nuclear structure from master-level courses • Teaching experience Language requirement:​ • Good oral and written communication skills in English • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 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 For more information see: The purpose of the fellowship is research training leading to the successful completion of a PhD degree.  All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation. What are we looking for in you?​ Personal skills:​ • Ability to work both independently • Good communication skills • Ability to work in an international research environment Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications. We can offer you​ • A pleasant and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund  We need different perspectives in our work​ UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here.  We hope you will apply for the position with us. 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 educational certificates, academic transcript of records and documentation of English proficiency if applicable • 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) Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system. When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information​ The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.   The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.

University of Oslo

About the position​ Position as PhD Research Fellow in High-Performance Computing available at Department of Informatics. The fellowship period is three years. Depending on the candidate and the teaching needs of the department, the fellowship period can be extended either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up top four years. Starting date no later than October 1, 2026. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Place of work is Department of Informatics at Blindern, Oslo. Job description​ This PhD project aims to study the convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use of AI and in particular machine learning (ML).  As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC should be used in this context. The general research question is: “How can HPC fur-ther enhance AI/ML, and vice versa?” Working closely with the staff of the newly established HPC research group at the Department of Informatics and their collaborators (Simula, Inria, Lawrence Berkeley National Lab, University of Tokyo etc.), the PhD candidate is expected to research on some of the following themes: • New algorithms for parallel/distributed AI/ML • Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML • Optimization of process-to-process communication in parallel/distributed AI/ML • Enhancement of AI/ML with in-network computing & processing • Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures • Physics-informed ML surrogates for efficient simulation • ML-supported optimization of HPC software What skills are important in this role?​ 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 HPC and/or ML • Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system • Fluent oral and written communication skills in English  Candidates without a master’s degree have until June 30, 2026 to complete the final exam. Desired qualifications:​ • Good programming skills • Knowledge about hardware technologies • Experience with using supercomputers • Experience with scientific writing and publication Language requirement:​ • Good oral and written communication skills in English • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 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 The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation. What are we looking for in you?​ Personal skills:​ • Ability to work both independently and as part of a team • Ability to work precisely in a structured manner • Ability to think innovatively • Good communication and collaboration skills • Positive attitude and the ability to handle hectic periods • You are a person who prefers being present at work and actively contributes to the professional and social environment you are a part of Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications. We can offer you​ • A pleasant and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund  We need different perspectives in our work​ UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here.  We hope you will apply for the position with us. How to apply​ The application must include:​ • Cover letter - statement of motivation and research interests • CV (summarizing education, positions and academic work - scientific publications) • Transcripts of records, copies of the original Bachelor and Master’s degree diploma (see below) • Letters of recommendation • Documentation of English proficiency if applicable • List of publications and academic work (if any) 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) Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system. When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information​ The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.   The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.