Postdoctoral fellow within Hyperspectral Imaging for Tree Ring Characterization
Deadline: 30.10.2024
Publisert
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About The Faculty of Environmental Sciences and Natural Resource Management
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.
Are you an expert in hyperspectral imaging and seeking a new challenge? Join our research project!
About the position
Faculty of Environmental Sciences and Natural Resource Management (MINA) at Norwegian University of Life Sciences (NMBU) has a vacant three-year postdoctoral position related to the detection and characterization of tree rings using hyperspectral imaging technology.
We are seeking a post-doctoral fellow with expertise in Hyperspectral Imaging (HSI) to join our project entitled "Novel Approach to Dendroclimatology Using Hyperspectral Imaging and Deep Learning". The project is funded by the Human Frontier Science Program (HFSP). For further details, see here.
The project aims to apply cutting-edge analytical technologies to dendroclimatology, with a specific focus on tropical tree species.
Dendroclimatology, the study of tree rings to extract past climate proxy data, is key to climate research, especially in temperate and boreal regions with clear seasonal patterns. However, in tropical areas, tree ring formation is more complex due to less defined seasons and climate variability. Consequently, climate records from tropical regions, especially in Africa, are scarce, highlighting the need for improved technologies to analyze tree rings and advance the continent’s climate science.
In this project, we aim to pioneer a novel method in dendroclimatology by combining Hyperspectral Imaging (HSI) and Deep Learning (DL) for detecting, characterizing and consequently extracting climate proxy information from tree rings. We will analyze samples from tropical tree species, aiming to advance climate research in tropical regions through the use of these cutting-edge technologies.
If you have a strong interest in climate research and a background in HSI, we encourage you to apply.
Main tasks
Exploring different HSI systems to understand their capabilities and limitations for detecting tree rings.
Examining sample preparation techniques for imaging, including polishing to enhance clarity and accuracy in the analysis.
Assessing instrumental setup techniques, including the camera angle, distance from the sample, and any required filters or lenses to capture high-quality images.
Writing and publishing scientific papers in peer-reviewed journals.
Presenting project results in workshops and conferences.
Collaborating with project members, including a PhD candidate and postdoctoral fellow, in a multidisciplinary environment that integrates hyperspectral imaging, data science, and dendroclimatology labs across Norway and Ethiopia.
Determining the best lighting conditions, such as light intensity and wavelength, to highlight the characteristics of tree rings from different types of wood samples.
Applying these techniques and setups outside a controlled lab environment for field analysis of wooden samples.
Competence
Required Academic qualifications
A PhD in Remote Sensing, Physics, or related fields.
The following experiences and skills will be emphasized:
Expertise in hyperspectral imaging techniques.
Experience with instrumental setup for data collection and preparation.
Experience with hyperspectral imaging of wood samples.
Experience with using hyperspectral imaging in the field.
Experience with various types of data analysis, especially image data.
Proficiency in programming, particularly Python.
Proven experience in writing and publishing scientific articles in international peer-reviewed journals.
Experience working on collaborative academic and research projects.
The following experiences and skills will be considered advantageous:
Familiarity with basic tree physiology and climate science
You need to:
Have strong oral and written communication skills in English, with the ability to collaborate effectively in interdisciplinary and international teams.
Have proven ability to foster a welcoming, productive work environment and thrive in a multidisciplinary, global setting.
Have high work capacity and enthusiasm for teamwork.
Remuneration and further information
The position is placed in government pay scale position code 1352 Postdoctoral Fellow, salary grade 62-77 (604900-796600) depending on qualifications. The position follows ordinary meriting regulations.
To apply online for this vacancy, please click on the 'Apply for this job' button above. 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: 30.10.2024
Your CV must be entered in JobbNorge'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.
Up to ten publications selected by the applicant as most relevant must be attached to the application. If it is difficult to identify the contribution of the applicant in multiple-author publications, a short explanation about the applicant’s part of the work is suggested.
Printed material which cannot be sent electronically should be sent by surface mail to Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, within 06.11.2024. Please quote reference number 24/04895.
Applicants invited for an interview will be asked to present verified copies of diplomas and certificates.
Please note that the report from the expert committee will be sent to all applicants.
