
NTNU - Norwegian University of Science and Technology · Trondheim
This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three ci...
NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.
At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.
You will find more information about working at NTNU and the application process here.
aiD – AI for Decisions – is one of Norway's new national AI research centers, funded by the Research Council of Norway and industry partners. Led by NTNU and SINTEF, the center brings together 13 research partners and more than 60 partners from industry and the public sector. All open positions will be cross-linked on the aiD website aid-center.no
The successful applicant will work at NTNU in Trondheim. The Department of Mathematical Sciences, NTNU, will host the PhD position. The topic of the PhD fellowship is at the interface of numerical mathematics, agentic and generative AI models, and computer science. A successful candidate will be offered a three-year position, which could potentially be extended with career promotion work like teaching duties.
Are you motivated to take a step towards a doctorate and open exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.
Your immediate leader will be the Head of Department.
Many critical decisions in science and engineering, from managing power grids to planning subsurface energy operations, depend on computational models that are inherently uncertain. Uncertainty quantification (UQ) seeks to characterize and propagate this uncertainty but translating it into actionable risk measures remains computationally demanding and methodologically challenging. In realistic applications, uncertainty arises from multiple sources, including parametric uncertainty, model-form and structural assumptions, numerical discretization, and incomplete or noisy observations. Addressing these uncertainties typically relies on ensemble-based simulations using computationally expensive high-fidelity models.
This PhD project addresses this challenge by researching agentic programming frameworks for decision-oriented uncertainty and risk quantification, in which multiple specialized AI agents collaborate to design, execute, and evaluate UQ workflows under computational constraints. Rather than automating predefined pipelines, the agents act as meta-decision-makers, reasoning about modelling assumptions, approximation levels, and the choice of risk measures considering both decision objectives and available resources.
The central scientific aim of the PhD project is to establish formal links between uncertainty representations, risk measures, and downstream decisions, and to study how agentic reasoning can navigate trade-offs between interpretability, statistical reliability, and computational feasibility – and to develop principled criteria for when a given risk measure is well-founded given available data and resources, and when alternative approximations should be considered.
Duties of the position
Be prepared for changes to your work duties after employment.
Required selection criteria
PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”.
The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.
It is an advantage if you have experience with one or more of the following topics:
It is also an advantage if you have experience with publication-oriented research work and collaboration in international research environments.
Knowledge of Norwegian or another Scandinavian language is beneficial but not required.
To complete a doctoral degree (PhD), it is important that you are able to:
Emphasis will be placed on personal qualities and motivation for the position.
We offer
As a PhD Candidate at NTNU, you will have access to employee benefits.
Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.
We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.
If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time.
At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.
In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.
The employment period is 3 years for the doctoral work. The department might in addition offer upto 1 year of career promotion work.
For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in (https://www.ntnu.no/studier/phma) within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment.
The position is conditional on external funding.
As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.
For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.
The appointment is carried out in accordance with the principles of the State Employees Act, and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to be in conflict with the criteria in the latter act, will not be able to be employed.
The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in English or a Scandinavian language.
Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here. If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir), please attach this as well.
Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation.
When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.
NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).
A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the exemption is not granted.
If you think this position looks interesting and in line with your qualifications, you are welcome to apply.
If you have any questions about the position, please contact Trond Kvamsdal, Professor at Department of Mathematical Sciences, NTNU through e-mail: Trond.Kvamsdal@ntnu.no or Chief Scientist Knut-Andreas Lie at Department of Mathematics and Cybernetics, SINTEF Digital, through e-mail: Knut-Andreas.Lie@sintef.no.
If you have any questions about the recruitment process, please contact Lisa Wedershoven, e-mail: lisa.wedershoven@ntnu.no.
For practical information about working at NTNU, please visit this webpage.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
About the positions Interested in pursuing a PhD in machine learning in an interdisciplinary and collaborative environment in Norway? Integreat - Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo and UiT The Arctic University of Norway invites applications for eight PhD fellowships connected to interdisciplinary projects in knowledge-driven machine learning. Four of the positions are co-funded with TRUST - The Norwegian Centre for Trustworthy AI. Integreat and TRUST provide a broader interdisciplinary research environment, offering all recruited candidates access to complementary expertise, scientific activities, and national research networks. The purpose of the fellowships is research training leading to the successful completion of a PhD degree. Successful applicants will be enrolled in the PhD programme at the University of Oslo or UiT The Arctic University of Norway. Integreat brings together more than 100 researchers from mathematics, statistics, machine learning, logic, language technology, philosophy, and related fields. As a PhD fellow, you will become part of this interdisciplinary research community and work closely with researchers at different career stages across Integreat's partner institutions. You will also join an established cohort of early-career researchers and benefit from the centre's researcher development programme, including scientific seminars, interdisciplinary workshops, mentoring, career development activities, research mobility support, and social events. The duration of each fellowship is specified in the individual project description. Most positions are three-year appointments. For selected projects, a four-year appointment may be offered, where the additional year is devoted to career-promoting tasks such as teaching, supervision, or other research-related duties outside the PhD project. Starting date by agreement, depending on the project. The place of work, either in Oslo or in Tromsø, is specified in each project description. Working language: English Integreat and TRUST About Integreat Integreat – Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence funded by the Research Council of Norway, with branches in Oslo at the University of Oslo and in Tromsø at UiT The Arctic University of Norway. Machine learning is a core driver of artificial intelligence (AI) and an increasingly important force in a digital and data-driven world. Integreat develops theories, methods, models, and algorithms that combine data with general or domain-specific knowledge, helping lay the foundations for the next generation of machine learning. Integreat projects aim for more accurate, more sustainable, more explainable, and more trustworthy machine learning, with quantified uncertainty. The centre brings together perspectives and methodologies from statistics, logic, language technology, theoretical computer science, ethics, and machine learning in new ways. Its research focuses on developing ground-breaking methods and theories for addressing fundamental challenges in science, technology, health, and society. Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, and Philosophy, the Oslo Centre for Biostatistics and Epidemiology at UiO, the Norwegian Computing Center (NR), and the machine learning group at UiT, with members from the departments of Physics and Technology, Mathematics and Statistics, and Computer Science. About TRUST TRUST is a Norwegian research centre dedicated to building the foundations of trustworthy AI. Its mission is to enable AI systems that are accurate, interpretable, inclusive, fair, safe, sustainable, and well-governed. By uniting expertise from (i) machine learning, statistics, mathematics and data science, (ii) law, and social sciences, and (iii) philosophy, the centre seeks to produce ground-breaking results tested on real-world problems, including healthcare, mobility, governance, security, and climate resilience. In advancing trustworthy AI, TRUST will develop new AI technologies, support innovation, and investigate the societal consequences of AI, including the effects of AI on democracy, science, and the environment. With a consortium of over 70 partners from academia, industry, government and civil society in Norway and internationally, TRUST’s research is theoretical, methodological, legal, and empirical. TRUST is funded by the Research Council of Norway and its public and private partners, and is led by the University of Oslo, SINTEF and the Norwegian Computing Center (NR). Integreat and TRUST collaborate on selected research and training activities, creating opportunities for interaction across complementary research areas in machine learning and trustworthy AI. Through access to the scientific activities, expertise, and networks of both centres, recruited candidates will benefit from opportunities for scientific exchange, interdisciplinary collaboration, engagement with academic and non-academic partners, and participation in a wider national AI community. About Integreat See the information video for more information about Integreat. Video: https://www.youtube.com/shorts/-_I52cJHiW4Job description Integreat seeks to recruit fulltime PhD fellows for eight cross-disciplinary projects spanning machine learning, statistics, logic, language technology, and ethics. The projects address fundamental challenges in modern machine learning and contribute to developing new theoretical and methodological foundations for the field. As a PhD fellow, you will conduct independent research within one of the advertised projects under the supervision of leading researchers. You are expected to contribute actively to the research environment by participating in the centre's scientific activities, seminars, workshops, and collaborative initiatives. Detailed information about each project, including the host department, PhD programme, starting date, and project-specific qualification requirements, is provided below and in the links. Project descriptions Project 1: Predictive Bayesian inference and foundation models • Employment: University of Oslo, Department of Mathematics • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter Project 2: Bridging logic, knowledge representation and learning • Employment: University of Oslo, Department of Informatics • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter Project 3: Data attribution for LLMs • Employment: University of Oslo, Department of Mathematics • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences Starting date: preferably in 2026, by agreement Project 4: Measuring bias in VLMs • Employment: University of Oslo, Department of Informatics • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences Starting date: preferably in 2026, by agreement Project 5: Models and dynamics of machine reasoning • Employment: UiT - The Arctic University of Norway, Department of Physics and Technology • PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology Starting date: preferably in 2026, by agreement Project 6: Multi-agent knowledge bases • Employment: UiT - The Arctic University of Norway, Department of Physics and Technology • PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology Starting date: preferably in 2026, by agreement Project 7: Probabilistic Representation Learning • Employment: UiT - The Arctic University of Norway, Department of Physics and Technology • PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter Project 8: Structured VLMs: panoptic scene graphs for high-level reasoning • Employment: University of Oslo, Department of Informatics • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter Online information meeting We warmly invite prospective applicants to an online information meeting where representatives from Integreat and TRUST will introduce the research centres, present the PhD opportunities, and explain the application process. You will also have the opportunity to ask questions. Attendance is optional but strongly encouraged. • Date: Wednesday 22 July 2026 • Time: 19.00-20.00 CEST • https://uio.zoom.us/j/61927781301 Requirements Qualification requirements consist of three components: (i) general qualification requirements applicable to all applicants, (ii) admission requirements for the relevant PhD programme, and (iii) project-specific requirements. Applicants must satisfy all applicable requirements for every project they rank. Employment and admission to the PhD programme are conditional upon successful completion of the Master's degree and submission of official documentation confirming that the degree has been awarded. Applicants who are in the final stages of completing their Master's degree may still apply. i) General qualification requirements These are requirements applicable to all projects: • Master's degree, or equivalent, in a field relevant to the ranked project For candidates with a foreign completed degree (M.Sc.-level), it must correspond to a minimum of four years in the Norwegian educational system. • Research interest in one or more of the research areas represented at Integreat, including machine learning, statistics, logic, language technology, ethics, mathematics, or another related field • Fluent oral and written communication skills in English ii) Project-specific requirements Each project has a set of project-specific qualification requirements that are necessary for successful completion of the project. Before ranking a project, applicants must review the corresponding project description and ensure that they satisfy the project-specific requirements. iii) PhD programme admission requirements The purpose of the fellowships is research training leading to the successful completion of a PhD degree. Applicants must satisfy the admission requirements of the PhD programme associated with the project(s) they rank. University of Oslo Applicants must satisfy the admission requirements of the PhD programme at the Faculty of Mathematics and Natural Sciences, University of Oslo. Education • Master's degree or equivalent education relevant to the ranked project(s). Foreign education will be assessed to determine whether it is equivalent to the relevant Norwegian degree requirements. Grade requirements • Bachelor's degree courses: average grade C or better • Master's degree courses: average grade B or better • Master's thesis: grade B or better For applicants with foreign education, grades will be assessed in relation to the Norwegian grading scale as part of the admission process. Further information about the UiO admission requirements UiT The Arctic University of Norway Applicants must satisfy the admission requirements of the PhD programme at the Faculty of Science and Technology, UiT The Arctic University of Norway. Education • Bachelor's degree of 180 ECTS and Master's degree of 120 ECTS, or an integrated Master's degree of 300 ECTS. Grade requirements • Average grade C (strong 3.0) or better for the Master's degree. • The Master's degree must include an independent research project (e.g. Master's thesis). Foreign education will be assessed in accordance with UiT's admission requirements. Further information about the UiT admission requirements English language requirements • UiO regulations: English proficiency • UiT regulations: English proficiency Personal skills We are looking for candidates who are curious, motivated to learn, and interested in tackling challenging scientific questions. You should be able to work independently while also contributing actively to collaborative research activities and the broader research community. Integreat brings together researchers from different disciplines, institutions, and career stages. We value openness to new perspectives, effective communication, and a willingness to engage across disciplinary boundaries. We are looking for candidates who contribute positively to a supportive, inclusive, and respectful research environment. 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, 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. Integreat is committed to equity, diversity, inclusion, and belonging, guided by our INTEGREAT principles (Integrity, Non-discrimination, Tact, Environment, Gratitude, Respect, Empathy, Accountability, Transparency). We embed these values in practice through inclusive hiring and structured evaluations, targeted mentoring and career development, and flexible work arrangements and accommodations to ensure everyone can thrive and contribute. We have a clear institutional commitment to gender equality and diversity, with dedicated initiatives and networks for women in science. We hope you will apply for the position with us. Evaluation and selection process Applications will be evaluated by expert committees appointed by the participating institutions. Applicants will be assessed against the general qualification requirements, the admission requirements of the relevant PhD programme, and the project-specific requirements for each project they rank and other relevant formal national and institutional regulations. Applicants will be evaluated separately for each ranked project based on their academic qualifications and background, research experience, motivation, potential for research, and personal suitability for the project and research environment. Where relevant and with the applicant's consent, the evaluation committee may also consider an applicant for other projects included in the call if the applicant's qualifications and research interests are deemed to be a strong match. Shortlisted candidates will be invited to an online interview. References may be contacted as part of the final assessment. We offer Research environment and career development • A unique interdisciplinary research environment at the forefront of knowledge-driven machine learning. • Opportunities to develop independent research questions while collaborating with leading national and international researchers. • Structured career development, including an individual professional development plan throughout the PhD period. • Mentoring and support tailored to early-career researchers. • Research mobility funding supporting international collaboration and research stays. Working environment • A vibrant, international, and collaborative research community. • A friendly, inclusive, and supportive working environment that values diverse perspectives and interdisciplinary exchange. • A family-friendly and flexible workplace. We recognise that researchers have different life situations and actively support work-life balance through flexible working arrangements and consideration of caregiving responsibilities when planning conferences, research stays, and travel. Living in Norway • Family-friendly surroundings in Oslo and Tromsø, with excellent opportunities for culture, nature, and outdoor activities. • A generous public pension scheme and social benefits. • Full access to the Norwegian National Insurance Scheme and public healthcare. • A strong institutional commitment to gender equality, diversity, and inclusion, supported by dedicated initiatives and networks for women in science. If you have to relocate to Tromsø, the Faculty of Science and Technology may reimburse your moving costs. Further details regarding this matter will be made available if you receive an offer. Salary and employment • Salary as a PhD Research Fellow (position code 1017) in the range NOK 550 800–595 000 per year, depending on competence and prior relevant experience. A statutory contribution of 2% to the Norwegian Public Service Pension Fund is deducted from the salary. • For UiT positions (Projects 5–7), the starting salary is normally NOK 565 000 per year, with an annual salary increase of 3%. How to apply • Submit one application through the electronic recruitment portal. • Rank at least one and up to three projects in order of preference to be considered. • Upload all required documents in the original language together with an official translation into English or a Scandinavian language, where applicable. Applicants with foreign education are advised to provide an official explanation of their institution's grading system. Required documents Name all files using this format: Surname-First name-DocumentType • Cover letter (DocumentType: CoverLetter) Describe your motivation, research interests, and interest in the selected project(s). • Curriculum Vitae (DocumentType: CV) Summary of your education, employment history, academic achievements, publications, and other relevant experience. • Official transcripts of records (DocumentType: BachelorTranscript and/or MasterTranscript) Include transcripts showing courses, credits, and grades, together with degree diplomas (DocumentType: BachelorDiploma and/or MasterDiploma) for Bachelor's and Master's degrees. • Master's thesis (DocumentType: MasterThesis) Upload your Master's thesis and any other academic work relevant to the application (DocumentType: AcademicWork). If your thesis has not yet been completed, upload a draft version. • Project-specific documentation (DocumentType: ProjectSpecificDocumentation) Documentation of qualifications required by the ranked project(s), where applicable. • Documentation of English proficiency (DocumentType: EnglishTest) Upload documentation of English proficiency, where applicable. • References (DocumentType: References) Provide the names and contact details of 2–3 references, including their relationship to the applicant, email address, and telephone number. Reference letters are not required. • Expected completion statement (DocumentType: ExpectedCompletionStatement) Required only for applicants who have not yet completed their Master's degree. Upload a statement from your supervisor or institution confirming the expected date of completion of the degree. Formal regulations Successful candidates will be employed by the relevant host institution and are subject to the regulations governing employment and doctoral education in the Norwegian public sector. All qualified candidates will be assessed in accordance with applicable national export control, sanctions, and security regulations. Appointment is subject to the outcome of these mandatory checks. Before commencement of employment, applicants must have completed their Master's degree and satisfy all relevant PhD admission requirements and be able to document that these requirements have been fulfilled, including any applicable English language requirements. University of Oslo 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. UiT The Arctic University of Norway Further information for applicants and relevant regulations are available on UiT's website. A shorter period of appointment may be decided when the PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position as PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years. We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to the Personal Data Act information about the applicant may be included in the public applicant list, also in cases where the applicant has requested nondisclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.
A position as PhD fellow in Environmental Radiochemistry is available at the Institute of Energy Technology (IFE) and the work will be conducted at the Institute for Energy Technology (IFE) and the Norwegian University of Life Sciences (NMBU) in Ås (Norway). The Institute of Energy Technology (IFE) is an independent research foundation in Norway, with locations in Kjeller and Halden. We are an internationally leading research environment that actively develops innovative solutions through people and technology. We operate under the mission “Research for a better future”. IFE is a broad interdisciplinary research organization with top-level international expertise in environmental technology, radiopharmaceutical technology and nuclear technology and safety, as well as digital technologies, material and process technology, flow and analysis technology. The Department of Environmental Safety and Radiation Protection (MIST) carries out analyses of radioactive substances in various types of sample materials (environmental samples, food and other commercial products) and has laboratories and measuring equipment for the analysis of samples with very small amounts of radioactivity. The department is one of Norway's largest in this field and is a qualified member of the IAEA's ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network. To be a qualified member here, the laboratory must participate with good results in so-called ALMERA proficiency tests organized by the IAEA. The Tracer Technology Department was established in 1980s and has been pioneer in research and development (R&D) of tracer technology. We performed the first injection of radioactive tracers in the Norwegian continental shelf (Ekofisk) in 1986. Today, we have extended our R&D competence and know-how on tracers for Oil & Gas Industry, tracers for geothermal applications, environmental monitoring, circular economy and applied nuclear technology. We have been active in the development of radionuclides for the pharmaceutical industry, and we are hosting a national infrastructure project. IFE is part of the Nuclear Research Centre (NNRC). The NNRC is a collaborative effort between IFE, University of Oslo (UiO), and NMBU to increase Norwegian competence and research capacity within the nuclear sciences. The position will have thematic relevance to the research theme 5 (RT) that focuses on environmental chemistry of radionuclides, and it is expected to interact with the RT4 that focuses on radionuclide production and speciation. At NMBU, the PhD candidate will be part of the Faculty for Environmental Sciences, which has leading international competence in the behaviour of radionuclides in the environment. The team consists of professors, researchers, and PhD students, with a large international network. Job description This PhD project will focus on transfer and mobility of artificial radionuclides (e.g. Pu, Cs-135, I-129, non-naturally occurring U isotopes) in contaminated environments. A special focus will be on site-specific factors that can alter radionuclide behavior, such as the cycling of redox-sensitive elements and microbially mediated processes in soils. The project integrates the radiochemical analysis with biogeochemical approaches, creating a state-of-the-art approach for understanding the mechanisms governing radionuclide mobility under environmentally relevant conditions. The project will also explore if any links in mobility exist between potential radionuclide contaminants and critical raw materials (e.g., rare earth elements) in the case of legacy waste sites. The completed project will increase the knowledge of radionuclide behavior under subarctic environments and contribute to improved practices within environmental monitoring and emergency preparedness. Qualification requirements- The applicant must hold a master’s degree in chemistry, radiochemistry, geochemistry, microbiology, or other environmental sciences of relevance. - Academic background relevant to environmental radiochemistry, radioecology, or radioactivity in the environment. - Experience from hands-on laboratory work, especially with respect to radionuclide separation and/or DNA extraction and purification from environmental samples. The following qualifications are considered desirable: - Experience with modeling and/or programming (e.g., geochemical modeling, dispersion modeling) - Practical skills in mass spectrometry and/or radiometric methods, previous work with radionuclides is advantageous but not essential. - Familiarity with environmental impact assessments and tools. - Experience with scientific publication. - Practical experience in fieldwork with environmental samples - Competence in statistics. - Solid written and oral communication skills in English, including academic writing. The applicant is made aware that an application for this PhD position is at the same time an application for admission to a PhD programme at the NMBU. Hence, applicants are advised to read the section Before applying| NMBU, with the NMBU PhD Regulations, the relevant MINA PhD programme description and requirements for documentation of English proficiency. The documentation that is necessary to ensure that the admission requirements are met should be uploaded with the application.Personal qualities• Motivated and engaging person within the professional area and towards the colleagues. • Proactive with a high degree of initiative, creativity, and curiosity. • The candidate should be highly independent, whilst also being able to work under the guidance of the project supervisors. • The candidate should be comfortable with handling responsibility within this project. • Strong awareness towards Health Safety Environment and Radiation protection regulations compliance.We offer IFE offers competitive salary, pension and insurance schemes, but above all we offer an opportunity for personal development that few others can offer. The position entails a opportunity to influence your development to become part of a larger community of specialists. You will be working in an interdisciplinary, international environment. You will be part of a stimulating work environment with skillful, experienced, and creative colleagues. Be able to come in contact with well-established national and international scientific and industrial networks How to apply The application must include: • A cover letter stating your motivation, research interests and scientific background. • A detailed CV. • List of publications and academic work that the applicant wishes to be considered by the evaluation committee. • Name and contact details of 2 – 3 references (name, e-mail address, telephone number, and relation to candidate) The application with all attachments must be submitted in English or a Scandinavian Language. Foreign applicants are advised to attach an explanation of their university’s grading system. IFE is subject to the Security Act, which includes requirements for the organisation’s management of critical national information, as well as other relevant legislation concerning the management of sensitive information. On this basis, it is a prerequisite for employment that the applicant is suitable from a security perspective. Note that relevant applicants will be asked questions that are necessary to ascertain this. This includes questions about any ties to countries that the PST has classified as a ‘high-risk country’ in its open threat assessment. Background checks are performed as part of our recruitment process. We view diversity as a strength in our work. We therefore encourage all qualified candidates to apply regardless of age, gender, disability, sexual orientation, religion and ethnic background. We place great emphasis on your personal suitability for the position. KontaktinformasjonDeborah Oughton, Professor in Nuclear Chemistry/Environmental Chemistry at NMBU, deborah.oughton@nmbu.no Cato Christian Szacinski Wendel, Researcher, Environmental Safety and Radiation Protection Department, IFE., Cato.Wendel@ife.no Niroshan Gajendra , Researcher, Tracer Technology Department, IFE., Niroshan.Gajendra@ife.no Ingrid Helen Hauge, Department Head, Environmental Safety and Radiation Protection, IFE, Ingrid.Hauge@ife.no ArbeidsstedInstituttveien 18 2007 Kjeller Nøkkelinformasjon:Arbeidsgiver: Institutt for energiteknikk (IFE) Referansenr.: 5134401754 Stillingsprosent: 100% Seasonal Startdato: 14.09.2026 Sluttdato: 13.09.2029 Søknadsfrist: 15.08.2026
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: MarTech Data Science Measurement empowers Airbnb to optimize marketing ROI through data-informed decision-making. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, Engineering, and Product to provide actionable recommendations and tools based on effective, timely, and granular measurements. The Difference You Will Make: We are seeking experienced Data Scientists to serve as technical anchors across our team’s two pillars. The ideal candidate combines depth in causal inference, experimentation, and customer relationship modeling with the ability to drive rigor in solutions and data-informed decision making across the team and our cross-functional partners. * Actionable: Deliver insights that drive confident business decisions. * Impactful: Prioritize projects based on their expected value to Airbnb. * Balanced: Adapt methods to business questions and data realities, acknowledging limitations. * Rigorous: Maintain methodological integrity and quantify the sensitivity of findings. * Innovative: Invest in advancing measurement science and developing new methods. * Influential: Share learnings across Airbnb and the broader data science community. A Typical Day: * Causal Inference: Apply and develop causal inference methods to estimate the effectiveness of Airbnb’s marketing initiatives. * Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts. * Experimentation: Design and analyze experiments to evaluate the impact of marketing campaigns. * Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies. * Thought Leadership: Lead the creation of internal white papers and contribute to Airbnb tech blog posts. Your Expertise: * PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience. * Deep knowledge of causal inference methodologies and experimentation techniques. * Proficiency in statistical programming (Python or R), database usage (SQL), and agentic coding. * Ability to communicate complex concepts clearly to stakeholders at varying technical levels. * Proven track record of solving business problems through data science methods. Preferred Expertise: * PhD in Economics, Statistics, Marketing, or a related field. * Passion for marketing and consumer science, with a desire to stay informed about the latest academic research. * Familiarity with Bayesian modeling and its applications in marketing. * Experience with causal ML modeling. * Experience in developing end-to-end models for data-driven decision-making. Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $151,000—$175,000 USD