Remote Sensing Specialists with Expertise in LiDAR, AI, and Ecology

4 hours ago


Aarhus, Denmark Aarhus Universitet Full time

Department of Ecoscience - Biodiversity and Conservation - Faculty: Technical Sciences

Remote Sensing Specialists with Expertise in LiDAR, AI, and Ecology

Deadline 3 Feb 2025, 23:59 CET

Expected start 1 Apr 2025

Department of Ecoscience - Biodiversity and Conservation C.F. Møllers Allé 8 8000 Aarhus C

Are you interested in remote sensing and LiDAR and can you contribute to the development of the digital monitoring of nature? Then the Department of Ecoscience invites you to apply for tenure track researcher / senior researcher position.

Job description

The Department of Ecoscience, Aarhus University is seeking tenure track researchers or senior researchers for positions to undertake research and consultancy within the field of remote sensing and vegetation structure and mapping with a special focus on LiDAR data. We are seeking a candidate with a background where remote sensing data is applied to biological/ecological purposes, ensuring an understanding of the challenges and potentials associated with using remote sensing to gather knowledge about vegetation and nature. The position will be placed in the Section for Biodiversity.

Responsibilities:

  • Strengthen the department's analytical and statistical capabilities, with a focus on remote sensing, LiDAR, AI tools, GIS, and spatial modeling.
  • Contribute significantly to the department's research and advisory profile on remote sensing, including the development of tools for Digital Nature Monitoring.
  • Collaborate with ongoing remote sensing activities and the topic center for terrestrial habitats and species to help build the next generation tools for biodiversity and biodiversity monitoring.
Your profile

We are seeking candidates who possess the following qualifications:

  • A PhD degree and an established track record of publications in high-impact, peer-reviewed international journals.
  • A broad publication record covering topics such as remote sensing, LiDAR point cloud analysis, GIS applications, and vegetation structure analysis.
  • Extensive experience in programming, particularly in Python, R, and GIS. The candidate must have experience with AI and, preferably, experience using deep learning with remote sensing data.
  • Significant experience with LiDAR and point cloud calculations. It would be a clear advantage if the applicant also has experience collecting point clouds using drones.
  • It would be a great advantage if the candidate has extensive experience with the practical application of remote sensing and LiDAR data for real-life monitoring, especially of vegetation or condition of natural areas. Experience in advising authorities would also be considered positively.
  • A certain knowledge of (or willingness to learn) Danish will be an advantage, as the job involves a significant amount of communication with Danish authorities.
Who we are

The Department of Ecoscience is engaged in applied research and advisory work for authorities covering the major biological subdisciplines. We conduct research in the areas of conservation biology and wildlife management, aquatic biology and ecology, and biodiversity. The Department currently employs approximately 275 academic and technical staff, as well as PhD students, distributed at two geographical locations in Aarhus and Roskilde. The Section for Biodiversity is situated in Aarhus and employs about 25 staff members.

What we offer
  • A well-developed research infrastructure and access to shared technical equipment
  • An exciting interdisciplinary environment with many national and international collaborators
  • A research climate encouraging lively, open, and critical discussion within and across different fields of research, a workplace characterized by professionalism, equality, and a healthy work-life balance.
Place of work and area of employment

The place of work is Department of Ecoscience, Aarhus University, C.F. Møllers Allé 8, bld. 1110, DK-8000 Aarhus C, Denmark.

Contact information

For further information, please contact: Head of Section, Beate Strandberg +45 30183151 ( ) or Senior Researcher Jesper Moeslund +4523227111 ( )

Deadline

Applications must be received no later than February 3rd, 2025.

Ensuring gender balance at the Department of Ecoscience is a high priority at Aarhus University, and therefore, we particularly encourage women to apply for this position. No candidate will be given preferential treatment, and all applicants will be assessed on the basis of their qualifications for the position in question.

Technical Sciences Tenure Track

Aarhus University offers talented scientists from around the world attractive career perspectives via the Technical Sciences Tenure Track Programme. Highly qualified candidates are appointed as Researcher for a period of six years with the prospect of performance-based advancement to a tenured position as Senior Researcher.

Application procedure

Shortlisting is used. This means that after the deadline for applications, the head of department selects the candidates to be evaluated based on who are most relevant considering the requirements of the advertisement. All applicants will be notified within 6 weeks whether or not their applications have been sent to an expert assessment committee for evaluation.

Formalities and salary range

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any).

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Questions about the position?

Jesper Erenskjold Moeslund Senior Researcher, Department of Ecoscience - Biodiversity and Conservation +4523227111 ( )

Deadline: Monday 3 Feb 2025 at 23:59 CET

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