Lund University, Department of Physical Geography and Ecosystem Science

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Post-doctoral fellow in Remote Sensing of rangeland productivity and biomass

Subject description
This employment concerns a postdoctoral fellow for two-year full time within the project Rangeland monitoring for Africa using Earth Observation - Continental Demonstrator (RAMONA) financed by the European Space Agency (ESA).

The project's goal is to develop and apply methodology for estimating biomass, primary productivity and vegetation phenology in African rangelands using passive and active Earth observation data. The project will create a continental demonstration project for Africa, based on data from the Sentinel satellites (1, 2 and 3). For rangelands in Africa we aim to quantify/estimate; (1) distribution and type of rangelands, (2) biomass and primary production (3) biomassa anomalies, (4) phenology and (5) ecological carrying capacity. Based on literature and collection of existing and new field data, algorithms will be developed and evaluated and then applied to the whole of Africa with a spatial resolution of 10 meters. The project is a collaboration with ESA, Aarhus University and two international commercial players

Work duties
The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning. This position is focussed on research. Duties include:

  • Compile and report a scientific overview of existing methods and algorithms for estimating biomass and primary productivity in rangelands based on soil observation data.
  • Develop and test new methods and algorithms for estimating biomass, primary productivity and other vegetation variables in rangelands based on time series from Earth observation data
  • Collaboration with other project participants, stakeholders in Africa and international organizations.
  • Participation in scientific meetings and workshops
  • If needed, perform field work and data collection in Africa.

Qualification requirements
Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed at the time for employment decision. The degree can be no more than three years old before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

  • Solid experience of remote analysis of vegetation properties, time series and light use efficiency methods
  • Very good oral and written proficiency in English.

Assessment criteria and other qualifications
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.

Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

  • A good ability to develop and conduct high quality research.

Experience and skills in especially optical remote sensing, especially with a focus on vegetation and time series analysis, but also skills in RADAR based remote sensing of vegetation. Experience and skills in plant science/plant ecology primarily focused on savannas and the processes that control the plants' photosynthesis/carbon storage. Experience and skills in data analysis (statistics, numerical analysis, time series analysis, etc.) Experience from application and development of ‘Light use efficiency’ models.

Additional assessment criteria:

  • Publications in international journals.
  • Other documented communication skills.
  • Driving license.
  • Experiences of field work.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
This is a full-time, fixed-term employment of a maximum of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008.

Instructions on how to apply
Applications shall be written in English and be compiled into a PDF-file containing:

  • Curriculum vitae / CV including list of publications.
  • A general description of previous research work and future research interests (maximum three pages).
  • Point-by-point account of how each criterion in the assessment basis above is met.
  • Contact information for at least two references.
  • Copy of diploma for doctoral degree and possibly other grades/certificates that you wish to invoke.
Type of employment Temporary position
Contract type Full time
First day of employment According to agreement for two years
Salary Monthly salary
Number of positions 1
Full-time equivalent 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2021/4165
  • Jonas Ardö, Professor, +46 46 222 40 31,
  • Tina Olsson, Human Resources Coordinator, +46 46 222 09 04,
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • SEKO: Seko Civil, 046-222 93 66
Published 02.Feb.2022
Last application date 01.Mar.2022 11:59 PM CET

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