NMBU skal bidra til å sikre fremtidens livsgrunnlag gjennom fremragende forskning, utdanning, formidling og innovasjon. Vi har landets mest fornøyde universitetsstudenter, som får forskningsbasert utdanning i et unikt studentmiljø. Våre kandidater får med seg høy kompetanse på tverrfaglig samarbeid og er populære i arbeidsmarkedet.
NMBU har internasjonalt ledende forskningsmiljøer innen flere fag. Sammen med våre partnere i samfunns- og næringslivet bidrar vi til å løse noen av de største samfunnsutfordringene i vår tid. Vi satser på innovasjon, formidling og entreprenørskap fordi vi mener disse utfordringene best løses med felles innsats.
Vi mener at et godt arbeidsmiljø preges av mangfold. Vi oppfordrer kvalifiserte kandidater til å søke uavhengig av kjønn, funksjonsevne, kulturell bakgrunn eller om du har vært utenfor arbeidslivet en periode. Vi vil legge arbeidsplassen til rette for personer med nedsatt funksjonsevne.
Nærmere opplysninger om NMBU finnes på www.nmbu.no
About the position
The Department of Data Science at Norwegian University of Life Sciences (NMBU), within the Faculty of Science and Technology(REALTEK), invites applications for a PhD position in Applied Causal Machine Learning. The position is affiliated with aiD, one of Norway’s national AI research centers focused on trustworthy, data-driven AI systems for critical industries.
The PhD position is for a period of 3 years, with a desired start date of 1st of October 2026.
aiD is a national flagship AI centre established to develop AI systems that humans can audit, understand, and trust. The centre works with applications in domains such as energy systems, health and medicine, logistics, infrastructure, and industrial operations.
The PhD project will focus on the intersection of machine learning, causal inference, and classical statistical methods. A central objective is to develop methods that move beyond correlation-based prediction toward causal reasoning, intervention-aware modelling, and interpretable AI systems. This transition from correlation to causation is considered a key challenge for trustworthy AI, particularly in settings where models support actions, interventions, and high-stakes decision-making.
The candidate will work in an interdisciplinary and collaborative research environment with opportunities for collaboration across academia and industry partners nationally and internationally
Main tasks
Pursue and complete doctoral training leading to the award of a PhD degree.
Undertake innovative and rigorous research on causal machine learning.
Disseminate research outcomes through scholarly publications and public engagement activities.
Collaborate with researchers and practitioners through the aiD network and related national initiatives.
Contribute to the scientific development and collaborative activities of the Data Science research group.
Participate in international research collaborations, conferences, and academic exchange opportunities.
The successful candidate is expected to enter a plan for the progress of the work towards a PhD degree during the first months of the appointment, with a view to completing a doctorate within the PhD contract period
Competence
Required qualifications
A Master's degree or equivalent in in statistics, machine learning, computer science, mathematics, physics, engineering, cybernetics, economics, data science, or a related field. Foreign degrees must correspond with the admission criteria for the PhD program.
In the Master’s degree, both the average grade point and grade on the Master’s thesis must be B or better in the Norwegian educational system. Applicants who have recently graduated with excellent results may be given preference.
Solid mathematics, including multi-dimensional calculus, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory
Familiar with machine learning and deep learning
Programming experience (Python or Julia) and their ecosystems (numpy, scipy, matplotlib)
Strong analytical and quantitative skills
Personal suitability and motivation for the position.
Qualifications considered an advantage
Experience with research on causality
Experience with advanced Bayesian statistics, optimization or graph theory
Experience with modern DeepLearning
Domain knowledge in one or more application field of aiD
Personal qualities
Curiosity
Ability to both work in groups and independent
Good collaboration skills and an ability to join interdisciplinary academic communities
Good communicative skills
Remuneration and further information
Salary in position as PhD Research Fellow, position code 1017, 550 800 NOK. For exceptionally well qualified candidates a higher salary may be considered.
By applying, the candidate confirms that information and documentation submitted via the job application may also be used by NMBU in a possible admission process to the PhD program. Admission to a PhD program is a prerequisite for appointment to the PhD position.
For professional and social interactions, the candidate is expected to be physically present at NMBU on a daily basis.
Send application electronically via the link "Apply for this job" at the top of this page. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Application Deadline: 31.08.2026
Your CV must be entered in Jobbnorge's CV form and not just included as an attachment. This is in order to be able to comply with the regulations to the Public Administration Act §15.
Interviews with the best qualified candidates will be arranged. Applicants invited for an interview are expected to present original diplomas and certificates.
The following documents must be attached to the application:
Motivation letter
CV
Certified copies of relevant academic diplomas and certificates. Diplomas, transcripts and diploma supplements that are not in Norwegian or English must be uploaded in the original language. An English translation of these documents must also be attached.
Applicants from universities outside Norway are kindly requested to send a diploma supplement, or a similar document, which describes in detail the study program and grading system.
Additional relevant documentation of professional knowledge (for example, list of scientific works). If it is difficult to judge the applicant’s contribution for publications with multiple authors, a short description of the applicant’s contribution must be included.
About The Faculty of Science and Technology
REALTEK is NMBU’s Faculty of Science and Technology, with strong interdisciplinary research environments spanning data science, machine learning, engineering, robotics, physics, mathematics, and sustainable technology development. The faculty emphasizes applied, solution-oriented research connected to societal and industrial challenges, particularly within sustainability, infrastructure, energy, and digital transformation.
The Department of Data Science is one of Norway’s early dedicated academic environments in data science and applied machine learning. The department combines expertise in machine learning, statistical modelling, scientific computing, optimization, and data management, with close collaboration across engineering and applied sciences at NMBU. Research activities are strongly application-driven and connected to real-world domains including healthcare, environmental systems, robotics, industrial processes, and sensor data analytics.
