Hogeschool PXL

Postdoc Researcher Wildland Fuel Type Mapping 100%

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Job Location

be, Belgium

Job Description

With more than 10,700 students and 1,300 staff members, PXL University of Applied Sciences and Arts is a leading institution in the region. In the dynamic network of PXL, we challenge every partner today to co-create the future. Rooted in identity and practice, we train entrepreneurial, engaged, and creative professionals and artists. We collaborate with organizations to develop solutions in research and services. We uphold a commitment to quality in an innovative and multidisciplinary environment that combines approachability with professionalism. PXL University of Applied Sciences and Arts has an external vacancy for the expertise centre PXL Bio-Research for a contractual assignment as: Job description The BIO-Research lab of PXL University of Applied Sciences and Arts and the sGlobe lab of the KU Leuven are seeking a highly motivated postdoctoral researcher to work on the BELSPO-funded FUELFUSION ‘Fusion of multi-scale and multi-sensor remote sensing for fuel type classification’ project. About the labs PXL BIO-Research aims to offer practice-oriented solutions in biodiversity policy and (urban) green management. In this context, we are conducting multiple research projects focusing on addressing the increasing demand for tools and expertise related to the inventory of ecosystems and their services using close-range remote sensing (including UAV and mobile platforms) in combination with deep learning. The sGlobe lab is part of the division Forest, Nature and Landscape of the KU Leuven. We aim to improve our understanding of the effects of global change on biodiversity and the functioning of terrestrial ecosystems. We combine big data with state-of-the-art modelling techniques, fieldwork and drone imagery to extract patterns and answer ecological questions on large spatial scales. More information? See www.sglobelab.com About FUELFUSION Wildfires have significant socio-economic and ecological impacts, posing risks to human lives, buildings, ecosystem services and biodiversity values. Areas with increased danger are being pushed north by climate change, resulting in an additional exposure of up to 15 million Europeans. However, integrated risk assessment systems for wildfires are still lacking in many industrialized countries. This project aims to facilitate bridging this gap by focusing on the accurate mapping of wildland fuel types in Belgium using diverse remote sensing techniques, exploiting the long experience obtained from similar ecosystems in Greece. Wildland fuels and their status (in terms of structure, vegetation composition, senescence and water content) are a prerequisite for any type of wildfire risk assessment framework, since they represent the biomass available for burning under the current meteorological conditions. Traditionally, fuel types have been estimated through time-consuming field observations, but recent advancements in satellite remote sensing and UAV technology in combination with multi-scale deep learning offer new opportunities. In particular, the design and implementation of novel methodologies for mapping fuel types based on the fusion of 3D point clouds and spectral data derived from UAVs – which is a research area that only recently has started being extensively investigated – offers great potential and will be the main focus of FUELFUSION. JOB DESCRIPTION You will closely collaborate with PhD students and research associates of both labs, and the project PI, dr. Sam Ottoy and prof. Koenraad Van Meerbeek. In addition, we foresee close collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki, and with prof. Ioannis Gitas and prof. Dimitrios Stavrakoudis in particular. You will collaboration in a dynamic and international scientific team where a healthy life work balance important is. The position will focus on the integration of data resulting from different sensors (RGB, multispectral, LiDAR) and platforms (satellite, airborne, UAV, mobile) to map wildland fuels at multiple scales. To this end, we will apply novel technologies based on the fusion of spectral and LiDAR data and multi-scale deep learning algorithms. In addition, the postdoc will be involved in capacity building and outreach to stimulate future research towards an integrated fire risk assessment in Belgium. Profile You hold a PhD degree in remote sensing (or in a related field) or you will have obtained it by the time you start working; You have strong expertise in terrestrial ecology and geospatial modelling; Proven UAV skills (flight mission planning, EASA drone pilot training,…) are a plus; You are an expert in programming languages such as R or python; You have proven abilities to publish at a high international level; You have a passion for nature and biodiversity; You are fluent in English, both written and oral; You are a team player with good communication skills. Offer Individuele hospitalisatieverzekering Tussenkomst openbaar vervoer Fietsvergoeding PXL University of Applied Sciences and Arts, centrally located in the heart of Limburg, is closely intertwined with the academic and economic life of the region. You can expect an engaging and challenging role with opportunities to take on responsibilities, while also having the chance to further develop your talents. You'll be part of an innovative and multidisciplinary environment that combines warmth with professionalism. You can look forward to an attractive holiday policy, reimbursement of commuting costs for public transport, a bicycle allowance, car rental via Cambio, a favourable hospitalization insurance plan, appealing catering conditions, and numerous other employee benefits. Tenure This contract starts in February 2025 and lasts for one year. After a positive evaluation, an extension of up to (maximum) one additional year may be granted. You will be based at PXL Bio-Research in Diepenbeek and the division Forest, Nature and Landscape in Leuven. Salary The classification is made according to the salary scale A22 (Assistant Lecturer / Doctor – Assistant). For more information, please refer to: https://onderwijs.vlaanderen.be/nl/onderwijspersoneel/hoger-onderwijs/personeel-hogescholen/salaris/salarisschalen-onderwijzend-personeel You can find the gross indexed monthly salary in the 'monthly salary' column. To calculate the gross-to-net amount , you can do so here. In addition to seniority in the public sector, relevant professional experience in the private sector or as a self-employed individual may also be recognized, in accordance with the decree on universities of applied sciences. The maximum recognized seniority for this position is 10 years , unless the automatically granted professional experience exceeds this limit. This relevant professional experience can be granted upon submission of the necessary documentation within one month of employment and after a thorough review of the complete file. The seniority provisions for internal candidates, as previously acquired, will remain in effect. HOW TO APPLY You can apply for this position until 03/12/2024, exclusively through our electronic application tool SES: https://ses.pxl.be. Through this platform, the application must be in Englisch and you can submit your CV and motivation letter (including the number of citations and H-Index from Google Scholar, a full list of publication, as well a copies of diplomas for Master’s and PhD degrees). You can be assured that your application will be handled with discretion. Procedure Notification of selection for interview based on CV and motivation letter is possible and depends on the number of applicants as from the beginning of December 2024. Candidates selected will be invited for an interview. The interview (online) is scheduled mid December 2024. Upon employment, you must meet the general admission requirements (admission requirements) as stipulated in the “Codex Hoger Onderwijs”. This vacancy will also be used to establish a talent pool. You can find more information.

Location: be, BE

Posted Date: 11/9/2024
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November 9, 2024
UID: 4927230150

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