PhD Research Fellow in Machine Learning and Data Fusion for Wildlife Detection - WILDETECT

Deadline: 03.12.2023

Western Norway University of Applied Sciences

With about 17,500 students, Western Norway University of Applied Sciences is one of the largest higher education institutions in Norway. A broad range of academic programmes are offered at Bachelor, Master and PhD levels, spread out on five campuses Førde, Sogndal, Bergen, Stord og Haugesund.

Our ambition is to build stronger and more solid academic and research environments that will interact nationally and internationally. The aim is to become a recognized actor on the international higher education arena. Increased international cooperation and engagement in externally funded projects will work towards this goal.

The Faculty of Engineering and Science has approximately 370 employees and approximately 3,260 students. The faculty has a broad educational offer at both bachelor's and master's level in engineering and science, as well as PhD education in computer technology. The Mohns Center for Innovation and Regional Development researches innovation and offers master's education in innovation and entrepreneurship. The diving education offers a one-year vocational school education.

The main part of the faculty's activities are in Haugesund, Bergen, Sogndal and Førde, but we also offer decentralized education in Florø, Kristiansund and Stord.

The faculty's activities are internationally based and take place in close collaboration with regional companies, clusters, health trusts and the public sector, including other institutions in the university and college sector. This applies to research, development, innovation and not least education with student projects at all levels.

PhD Research Fellow in Machine Learning and Data Fusion for Wildlife Detection with Drone- and Ground-Based Sensor Platforms 

The Department of Computer Science, Electrical Engineering and Mathematical Sciences at Western Norway University of Applied Sciences (HVL), has a vacancy for a research fellow (PhD position) in Machine Learning and Data Fusion for Wildlife Detection with Drone- and Ground-Based Sensor Platforms. The Fellowship will be part of the “WILDETECT: Exploring preconditions for an integrated safe and smart traffic environment system - for Wildlife collision avoidance.” project funded by the Norwegian Research Council.

The Research Fellow will be part of the HVL Robotics Lab, a research and innovation centre for robotics at HVL with strong industrial ties. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing at the Faculty of Engineering and Science. The research programme in Computer Science currently includes 20 professors and associate professors, more than 30 PhD and post-doctoral fellows, and a large number of master’s students.

Workplace is campus Førde.

About the PhD project:

The research topic addressed in the PhD project will be Machine Learning, Computer Vision, and Data Fusion for Wildlife Detection with Drone-and Ground-Based Sensor Platforms.

Over 15 thousand wild cervids were killed or injured on roads and railways in 2021 in Norway. The WILDETECT project aims to develop knowledge-based outcomes for the development of a safe and smart traffic system that can detect wildlife and warn road authorities and drivers of increased collision risk. The project results will be a starting point for developing future technology systems that can be applicable to traffic planning, providing road users with real and dynamic traffic information, thus contributing to increased transport safety.

The project is led by SINTEF and project partners are the Norwegian Institute for Nature Research (NINA), Western Norway University of Applied Science (HVL), the Norwegian Public Roads Administration (NPRA), and the IMSA Knowledge Company.

The focus of the PhD will be on exploring the design space of using ground- and drone-based image data, and advanced machine learning, for wildlife detection, collision prediction, and collision warning. This will range from the usage of ground- and drone-based sensory data, and data fusion, for direct warnings to drivers, to using the data for validating and augmenting existing statistical modelling frameworks. The image-based data will also be sought combined with weather/contextual data, and unstructured data from existing sources.

The work will include dataset design and gathering of RGB and thermal images of animals, and their tracks, and will aim to lay the foundations for a proof-of-concept ML pipeline for real-time wildlife detection and warning, which can also be fused with other sources of information, such as statistical models of animal movements. The work will involve usage of both aerial (drones, airplanes, etc.) and ground-based sensors for data gathering purposes, typically in high-density wildlife areas.

The PhD candidate will work closely with the project stakeholders to scope the work, and to iteratively test the algorithms and approaches developed.

Research environment

The PhD-candidate will be part of the HVL Robotics Lab, a research and innovation centre for robotics at HVL. HVL Robotics have access to state-of-the-art research facilities at Campus Førde, and a field lab for deployment of robots and sensors at Campus Sogndal/Leikanger.

The computer science research environment at Western Norway University of Applied Sciences has a strong focus on use-inspired and applied research, and on ICT as an enabling technology. The research environment has cooperation with many national and international research groups, and with national and regional industry partners. The research programme includes the research themes of software engineering, engineering computing, sensor networks and robotics, grid computing and physics data analysis, machine learning, and interactive and collaborative systems.

The PhD-candidate will work closely with the staff members of the HVL robotics group team and other staff members at HVL, associated with the “WILDETECT” project. The candidate will benefit from working together with colleagues with expertise on the intersection of robotics, sensors and machine learning across the HVL Robotics Lab, Ci2Lab, and the Data Science and Artificial Intelligence Group. The candidate will also collaborate with industry and stakeholder partners in the project, including expertise in wild animals (cervids in particular), statistical modelling, virtual reality, and road infrastructure. There will be a dedicated drone purchased for the project.

The PhD-candidate will receive an annual stipend to be used for conference participation, research visits, and equipment. Workplace will be at campus Førde, and the candidate should expect to travel between campuses for field work. The candidate may spend 3-6 months abroad at an international academic institution during the research period.


The PhD research fellow must hold a master's degree in Computer Science, Machine Learning, Electrical Engineering, or related field. Candidates who have submitted a master’s thesis (but who has not yet been awarded a master’s degree) may also qualify for the position provided that the master’s degree is awarded within 4 weeks after the application deadline. Previous experience working with image-based deep learning, sensor fusion, wildlife data, and drones/sensors, will be considered an advantage when candidates are ranked. Practical programming skills (e.g. Matlab, R, Python, etc) will be considered an advantage when candidates are ranked.

Candidates already holding a PhD within a related field are not eligible for this position. In addition to the required educational and scientific background, the following criteria will be evaluated: Relevant industry experience, competence and grades on completed course work, quality of the master's thesis (excellent grade, equivalent of grade B or better on the ECTS grading system), publications (if any), research and teaching experience, project management skills and experience. An outline of a research plan for the PhD project will also be taken into account when ranking candidates.

The candidate must be diligent and display the ability to work independently, supplemented with regular guidance, and is expected to carry out high-quality research and to publish the results in international workshops, conferences, and journals.

The candidate should be proficient in written and spoken English, and any formal training or proficiency in Norwegian or another Scandinavian language will be considered an advantage when candidates are ranked due to the close collaboration with Norwegian stakeholders in the project.

The PhD-candidate must enroll in the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing at Western Norway University of Applied Sciences, and must meet the formal admission requirements for admission into the PhD programme. An application for enrolment should first be submitted after an appointment is made and the supervisor(s) will help with this procedure. The candidate must be enrolled as a PhD student within 3 months from the start of the employment.

The position is for 3 years, with the possibility to extend the position into a 4-year position by further agreement where 25% of the work will be designated to teaching and other relevant work at HVL.

The ability to start the position timely after the project start (01. December 2023) will be considered an advantage when candidates are ranked due to the short time frame of the project.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to HVL.

Application procedure:

Applications will be evaluated by an expert panel of three members.

Applicants are asked to submit their application and CV online. Please use the link “Apply for this job” (“Søk stillingen”).

The following documentation should be uploaded as an attachment to the online application:

  • Transcripts of bachelor’s and master’s degrees
  • CV, with a complete list of any project work in industry and any academic publications
  • Master thesis if it is in English, or abstract of master thesis in English for Non-English thesis and candidates who have not yet submitted their master thesis within the application deadline
  • Diplomas and certificates
  • If any, copies of selected academic publications (no more than 3)
  • Optional: outline of research plan for the PhD project (no more than 2 pages)

Applicants should indicate which projects/publications or parts of projects/publications should be given special consideration in the evaluation. If the documents submitted are not in a Scandinavian language or in English, the applicants must submit certified translations of these. The transcripts must specify the topics, the course works, and the grades at the bachelor`s and master`s degree levels.

Applicants should note that the evaluation will be based on the documentation submitted electronically via Jobbnorge within the submission deadline. The applicants are responsible for ensuring that all the documentation is submitted before the closing date. It is of utmost importance that all publications to be considered in the evaluation are uploaded as an attachment with the application, since these are sent electronically to the expert panel. Applications cannot be sent by e-mail or to individuals at HVL.


  • Good occupational pension, insurance and loan schemes from The Norwegian Public Service Pension Fund
  • Exciting academic environment with the possibility of competence enhancement and development
  • Opportunities for training within the working hours 

Initial salaries will be offered at grade 54 (code 1017) in the Civil Service pay grade table scale.

There is a compulsory 2 % deduction to the pension fund (see http://www.spk.no for more information). The successful applicant must comply with the guidelines that apply to the position at any time.

General information:

The appointment will be made in accordance with the regulations for State employees Law in Norway ("Lov om statens ansatte)". Organizational changes and changes in the duties and responsibilities associated with the position must be expected.

State employment shall reflect the multiplicity of the population at large to the highest possible degree. Western Norway University of Applied Sciences Bergen has therefore adopted a personnel policy objective to ensure that we achieve a balanced age and gender composition and the recruitment of persons of various ethnic backgrounds.

Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. The applicant will be notified if his/her request is not respected.

Short-listed applicants will be called in for an interview.

Employed on condition that you are granted a work and residence permit (must be considered individually).

Western Norway University of Applied Sciences is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications. 


1) Associate Professor Martin F. Stølenphone: +47 57 72 25 03email: Martin.Fodstad.Stolen@hvl.no

2) Professor Håvard Helstrupphone: +47 55 58 75 61email: Havard.Helstrup@hvl.no

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