PhD Research Fellow in Ecology / Monitoring of Biodiversity

Universitetet i Sørøst-Norge
PhD Research Fellow in Ecology / Monitoring of Biodiversity


About the position

The Faculty of Technology, Natural Sciences and Maritime Sciences has a vacancy for a 100% position as PhD Research Fellow in Ecology from 01.06.2024.

The position is located at the Department of Natural Sciences and Environmental Health, and the immediate superior is the Head of the Department. The main work place is in Bø, in the Municipality of Midt-Telemark, Telemark County, Norway.

The appointment is for a duration of three years without teaching requirement. Depending on the Department's needs and the applicant's competence, a four-year appointment duration with a 25 % teaching requirement can be considered. There is a premise for employment that the PhD Research Fellow is enrolled in USN’s PhD-program in Ecology within three months of accession in the position.

About the PhD-project

“Monitoring wildlife integrating camera trapping, citizen science, artificial intelligence and hierarchical models accounting for uncertain classifications.”

The PhD project is part of the  “WildIntel” project, which has received funding via the European Commission’s Biodiversa+ Joint Research Call 2022-2033 “Improved transnational monitoring of biodiversity and ecosystem change for science and society (BiodivMon)”and the Norwegian Research Council (NFR), with cooperation partners from the Polish Academy of Sciences, Krakow, Poland, University of Huelva, Spain, Poland, Spain, and the German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, Germany.

WildIntel aims to develop a cutting-edge transnational protocol and workflow, leveraging artificial intelligence (AI) for wildlife and biodiversity monitoring. This initiative uniquely combines camera trapping, citizen science, convolutional neural networks, and hierarchical models to obtain unbiased demographic estimates of species and communities. We focus on mammals as sentinels of ecosystem health and condition.

Using AI methods or Citizen Science to classify images from remote cameras may result in significant biases. For instance, images captured at night often have poor visibility, making it difficult to accurately recognize and identify animals or species. Similarly, images featuring multiple animals can complicate the distinction between individuals. These limitations can adversely affect the accuracy of critical ecological measurements such as occupancy, abundance, and density. Despite their impact, these biases are frequently overlooked in the scientific literature, leading to potentially misleading conclusions about biodiversity estimates.

The main goal of the proposed PhD project is to estimate the effect of these biases on measures of biodiversity and propose methods to improve biodiversity monitoring. We will do this by modelling the uncertainty/error distribution to obtain unbiased estimates of occupancy- and abundance-related parameters in a hierarchical modelling framework.

The following research questions are proposed:

1. What is the effect of uncertainty in artificial intelligence (AI) classifications of remote camera pictures on species occupancy (i.e., the presence probability of a species) in a given area at a given time?

2. What is the effect of uncertainty in artificial intelligence (AI) classifications of remote camera pictures on the abundance of wildlife (i.e., the number of individuals of a species) in a given area at a given time?

3. What is the effect of the spatial scale and habitat features on the occupancy and abundance of the mammal community in different study areas?

Publication of research results in international peer-reviewed journals is expected.

The primary supervisor will be Prof. Andreas Zedrosser at USN, Prof. Nuria Selval from the Polish Academy of Sciences, and PhD Simone Santoro from the Universidad de Huelva. The applicant will be part of the research group EcoHub at USN and a member of the WildIntel team and project.


Applicants to the PhD position must have a Master’s degree (120 ECTS) equivalent higher education qualifications in Ecology or related areas.The degree must be accomplished before application deadline.

It is a requirement that the successful applicant is granted admission to the university’s doctoral programme in Ecology within three months of accession in the position. For admission to the Program, the candidate must have a grade B (weighted average) or higher in his/her Master’s degree or equivalent higher education.

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

The successful candidate should have:

  • Qualifications in the field of ecology or quantitative ecology.
  • A solid background in statistics, with the ability to handle and analyze large spatio-temporal datasets from remote camera sampling. The successful candidate should be familiar with hierarchical modelling in frequentist and Bayesian frameworks or at least possess the fundamental knowledge to quickly learn and effectively implement these techniques.
  • High proficiency in using R, with additional knowledge of Bayesian statistical environments like NIMBLE, STAN, or JAGS being highly valued.
  • Good oral and written English skills.
  • The ability to work independently and at the same time have the motivation to share knowledge and take part in team work.
  • The willingness to cooperate with other PhD students, postdoctoral researchers, and researchers in an international setting, including spending some of the PhD period with other WildINTEL’s partners.

An ideal candidate should be creative, analytical, highly self-motivated, and possess good collaborative skills. Demonstrable skills in publishing scientific papers and experience analyzing large data sets are advantageous but not required. The faculty staff work within subject teams to a large extent and the candidate must be motivated to share their knowledge and engage in a cooperative effort. Personal suitability for the position will be emphasized.

We offer
  • A stimulating and growing research environment, with good opportunities to develop your career and your academic skills
  • A good social environment
  • Attractive welfare benefits in the State Pension Plan
  • Opportunity for physical activities within working hours
  • Excellent opportunities for outdoor activities and a lively student community oncampus


PhD Research Fellow (code 1017): NOK 532 200 a year. Further promotion will be based on time served in the position. In special cases, employment in code 1378 (NOK 532 200 – 667 700 a year) may be considered.

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

Other information

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

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

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

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

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

Contact information

For more information about the position, please contact:
Professor Andreas Zedrosser, / +47 35 95 27 65

For questions regarding the recruitment process, please contact:
Head of Department Live Semb Vestgarden, / +47 35 95 27 97

How to apply

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

The following documents shall be attached to the online application:

  • Transcripts and diplomas of Bachelor's and Master's Degrees (120 ECTS)
  • A letter of motivation (maximum 2 pages)
  • Any scientific publications and a list of these
  • Three references (contact information)

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

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

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

Gullbringvegen 36, 3800 Bø i Telemark
Forskning/Stipendiat/Postdoktor, Annet, Ingeniør
Sist endret
28. feb. 2024 03:02