Research fellow - Multimodal AI for mapping biodiversity in forests

Norway | Sept. 23, 2026

Report as Closed

Company: EURES

Country: Norway

Type: Onsite

Employment: Contract

Description: Key information

Landsskogtakseringen is looking for a PhD candidate who will develop ground-breaking multimodal methods within artificial intelligence for mapping and monitoring biological diversity in forests. The project will investigate how heterogeneous information sources, including remote sensing data, forest inventory data, existing forest maps, environmental and climate data as well as new large-scale AI representations, can be used together to characterize forest ecosystems and their biological diversity.

The research will focus on developing multimodal learning methods that combine complementary information about forests across data sources, spatial scales and time dimensions. A central scientific challenge will be to learn integrated representations of forest ecosystems from datasets with very different characteristics, resolutions, geographical coverage and degree of supervision. These representations will then be used to fill important knowledge gaps related to biodiversity, with particular emphasis on mapping natural forests and important habitat types for biodiversity at a regional and national level.

The position is for three years with a place of work at NIBIO's head office in Ås, approximately 30 km south of Oslo.

The candidate will be admitted to a doctoral program at the Norwegian University of Environmental and Biosciences (NMBU) and will become part of the emerging the AI for Nature research environment, which is being developed in collaboration between NIBIO and NMBU.

A little about the framework for the position

The candidate will have access to supervisors from both NIBIO and NMBU.

The position provides a unique opportunity to conduct basic research in artificial intelligence while working with issues of great societal and environmental importance. The candidate will gain access to comprehensive national forest datasets and geographic information, work in an interdisciplinary research environment and contribute to the development of the next generation of AI methods for large-scale monitoring of forests and biological diversity.

To be a qualified applicant, you cannot have previously held a fellowship position at NIBIO, nor can you have a PhD from before or have previously held a fellowship position funded by the Research Council of Norway.

If you do not speak Norwegian, Swedish or Danish at a level A2 upon employment, NIBIO will offer free Norwegian training with the aim of achieving at least this level.

Main tasks of the position

The doctoral project will explore new methods of learning from several complementary sources of forest and environmental information. The research will move beyond models based on individual data sets, and investigate how multimodal artificial intelligence can integrate information from several data sources to describe forest properties that cannot be observed or measured satisfactorily through a single source alone.

The most important tasks will be to:

• Develop multimodal methods for deep learning and representation learning that integrate heterogeneous forest and environmental data sets, including remote sensing data, observations from forest inventories, existing forest maps, climate and environmental variables as well as large-scale geospatial representations generated using artificial intelligence
• Investigating methods for combining information across different spatial resolutions, time scales and data modalities, including situations where some data sources are incomplete or unavailable
• Exploring the use of foundation models and self-supervised learning to extract transferable representations from large-scale data sets in forest and soil observation
• Develop AI models for prediction and mapping of natural forest, important habitats for biodiversity and other ecologically relevant forest properties
• Integrate ecological knowledge and biodiversity observations in model development and evaluation
• Evaluate the models' generalizability and transferability between different forest types, environmental gradients and geographical regions
• Produce regional and national maps related to forest biodiversity and assess their accuracy and ecological relevance
• Publish results in leading international scientific journals and conferences, as well as contribute to collaboration between NIBIO, NMBU and national and international research partners

Qualifications

• Master's degree in machine learning, artificial intelligence, computer science, remote sensing, geomatics, data science or forestry and environmental studies with a strong quantitative or AI-related component
• Solid knowledge of machine learning and deep learning
• Good programming skills, preferably in Python and modern deep learning frameworks, such as PyTorch
• Experience working on large or complex datasets
• Good English skills, both oral and written
• You must meet the conditions defined for admission to relevant doctoral programs at NMBU

It is an advantage if you have

• Experience with multimodal learning, representational learning, self-supervised learning or foundation models
• Experience with geospatial data, remote sensing data and datasets based on citizen science
• Experience with work on heterogeneous datasets from various sensors or data sources
• Knowledge of forest ecology, biodiversity or applications in natural resource management
• Experience with development of reproducible research software and work in high-performance or GPU-based computing environments
• Experience with publication or contribution to scientific articles or conference contributions.

Personal qualities

• Good collaborative and communication skills
• Strong analytical abilities and good skills in problem solving
• Ability to work under pressure and handle demanding users and stakeholders
• Commitment to and motivation to contribute in an ambitious research environment
• Ability to collaborate effectively with internal and external experts with different professional backgrounds and expertise

We offer

• Opportunity to work on an important societal mission with a focus on sustainability and forward-looking projects
• Challenging, exciting and varied tasks in interdisciplinary teams
• A flexible everyday life with the opportunity to influence one's own work tasks
• A strong professional environment with good colleagues
• A generous personnel policy with welfare schemes and a focus on the employees' different life phases

The position is placed in the state salary regulations as a research fellow, job code 1017, annual salary NOK 555,000 - 635,000. Remuneration is assessed according to education and experience.

Membership of the Statens Pensjonskasse, which includes a good occupational pension scheme, occupational injury and group life insurance, as well as offers for home loans at favorable interest rates.

You can find more about NIBIO as an employer here: Job in NIBIO

How to apply for the position

Application with CV is filled out electronically and sent via the link on this page, "apply for the position".
Diploma and certificates are taken with any interview, or attached electronically.

NIBIO carries out a background check on relevant candidates.

Video: https://youtu.be/6mZySoUgD2QOther information

We emphasize diversity in the workplace and encourage qualified candidates to apply - regardless of age, gender, functional ability, gaps in CV, national or ethnic background.

As a state-owned enterprise, we have the opportunity to provide positive discrimination for applicants who have a disability, gaps in CV or immigrant background. Positive discrimination means, among other things, that you will get an interview more easily.
Read more about this here.

We point out that information about the applicant can be made public, cf. Act on the right to access documents in public undertakings (Public Affairs Act), § 25. An applicant can request to be exempted from entry on the public applicant list. If the request is not accepted, the applicant will be notified of this.

About the employer:

NIBIO works with agriculture, food, climate and environment. We deliver research, administrative support and knowledge for use in national preparedness, administration, business and society in general. NIBIO has its head office in Ås in Akershus, has approx. 750 employees, and is present in all parts of the country. NIBIO is owned by the Ministry of Agriculture and Food.

Odeling Landskogtakseringen collects data as a basis for national and regional forest statistics, prepares forecasts of forest resources and analyzes the condition and development of the forest.

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