Norges Miljø- Og Biovitenskapelige Universitet (nmbu)

Terje Gobakken

Professor

Rasmus Astrup

<h2>About the position</h2>The Faculty of Environmental Sciences and Natural Resources Management (MINA) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of &#34;SmartForest&#34; (<a href="https://www.smartforest.no" rel="nofollow">www.smartforest.no</a>), a center for research-driven innovation. The project focuses on using enabling technologies to support digitalized and sustainable forest management. We are now seeking a PhD candidate to support our work on developing improved methods using deep learning with 3D point clouds to characterize forest ecosystem structure and function. 3D point clouds from LiDAR and photogrammetry provide an excellent avenue to capture detailed data about forest ecosystems. To convert the captured data into meaningful information about the forest environment we seek a PhD candidate who wishes to advance state-of-the-art computer vision models for forest-based 3D point cloud data.In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek a candidate that can expand these methods to work for lower-resolution, landscape-level datasets.     The applicant is made aware that an application for a PhD position at NMBU is at the same time an application for admission to a PhD programme at the institution. The documentation that is necessary to ensure that the admission requirements are met must be uploaded as an attachment. <h2>Main tasks</h2>The PhD candidate will contribute to: <ul><li>Developing supervised deep learning algorithms for 3D point clouds </li><li>Developing self-supervised deep learning algorithms for 3Dpoint clouds </li><li>Expand for a wider variety of downstream tasks focused on characterizing forest structure and biodiversity</li></ul>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 scholarship period.  <h2>Competence</h2>Please note that an application for this position is also an application for admission to the PhD programme at MINA. The applicant must document: <ul><li>a strong and relevant academic background from previous studies, corresponding to a five-year Norwegian degree programme, with 120 ECTS credits at master&#39;s degree level. (Read about the ECTS credit system (europa.eu) ) </li><li>a master&#39;s thesis/ individual written assignment of at least 20 ECTS credits included in the degree. </li><li>an average grade corresponding to grade B or above in the ECTS grading system. </li><li>proficiency in both written and oral English. </li></ul>All applicants are advised to read the section <a href="https://www.nmbu.no/en/research/applying" rel="nofollow">Before applying | NMBU | NMBU</a>, with the NMBU PhD Regulations, the relevant MINA PhD programme description and requirements for documentation of English proficiency.The applicant must document expertise and interest in the research subject.Required Academic qualifications<ul><li>Master’s degree in machine learning, computer science, or a forest-related field with a focus on remote sensing</li><li>Experience with deep learning</li></ul>The following experiences and skills will be emphasized:<ul><li>Experience working with data from forest ecosystems</li><li>Experience with 3D point clouds</li><li>Strong programming skills and experience working with Docker and containerization</li><li>Proficiency in Norwegian or another Scandinavian language</li></ul>You need to have: <ul><li>Good interpersonal and communication skills</li><li>Strong analytical and problem-solving skills</li><li>Ability to work under pressure and interact with industrial partners </li><li>Commitment and enthusiasm for working as part of an ambitious research team</li><li>Ability to collaborate with both internal and external experts with diverse academic backgrounds and skills</li></ul> <h2>Remuneration and further information</h2>The position is placed in government pay scale position code 1017 PhD Fellow. PhD Fellows will normally have a starting salary of NOK 550 800. The position follows ordinary meriting regulations.Employment is conducted according to national guidelines for University and Technical College PhD scholars. For further information, please contact Professor Rasmus Astrup E-mail: rasmus.astrup&#64;nmbu.no; phone &#43;47 94151660 or Professor Terje Gobakken. E-mail: terje.gobakken&#64;nmbu.no; phone &#43;47 41512806.<a href="https://www.nmbu.no/en/research/applying" rel="nofollow">Information for PhD applicants</a> and <a href="https://www.nmbu.no/om/adm/poa/rekruttering/viktig-informasjon-for-s-kere/information-for-jobseekers-at-nmbu" rel="nofollow">Information to applicants</a> <h2>Application</h2>To apply online for this vacancy, please click on the &#39;Apply for this job&#39; button above. This will route you to the University&#39;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: 10.11.2025Your CV must be entered in JobbNorge&#39;s CV form and not just included as an attachment. This is to be able to comply with the regulations of §15 of the Public Administration Act.In the application, the candidate must confirm that information and documentation (in the form of attachments) submitted via the job application can also be used by NMBU in a possible admission process.Applicants invited for an interview are expected to present original diplomas and certificates. The following documents must be attached to the application:<ul><li>Motivation letter (maximum 1 page)</li><li>Complete CV </li><li>Certified copies of academic diplomas and certificates. (i.e. Diploma, transcript. Diploma supplement for both bachelor and master). 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.</li><li>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.</li><li>Documentation of proficiency in written and oral English in accordance with <a href="https://lovdata.no/dokument/SFE/forskrift/2020-01-30-1471" rel="nofollow">NMBU PhD regulation section 5-2 (3)</a>. </li><li>Names and contact details for two references</li><li>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.</li></ul> <h2>About The Faculty of Environmental Sciences and Natural Resource Management</h2>The Faculty of Environmental Sciences and Natural Resource Management (MINA) works with nature and the environment, sustainable use of natural resources, biological and geological processes.MINA’s employees undertake teaching, research and dissemination within the fields of geology, hydrology and limnology, soil science, environmental chemistry, forestry, ecology, natural resource management, renewable energy, and nature-based tourism.Our vision is to be a key actor in knowledge production and dissemination, and our goal is to deliver research of high, international quality, and varied and excellent teaching. The faculty’s employees are significant participants within their respective fields of expertise, both nationally and internationally. The faculty is dominated by a vital research culture and high levels of scientific production.The faculty has about 200 employees, 90 PhD students and 650 students.<a href="https://www.nmbu.no/en/faculty/mina" rel="nofollow">Read more about MINA here</a>.

PhD scholarship: methods for characterizing forest structure with deep learning and 3D point clouds