ORGANISATION/COMPANYHumboldt-Universität zu Berlin
RESEARCH FIELDEnvironmental science › Earth science
RESEARCHER PROFILEFirst Stage Researcher (R1)Recognised Researcher (R2)
APPLICATION DEADLINE18/04/2018 00:00 - Europe/Brussels
LOCATIONGermany › Berlin
TYPE OF CONTRACTTemporary
HOURS PER WEEK39
OFFER STARTING DATE01/06/2018
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / ERC
The successful applicant will study how data from Copernicus Sentinel-1 and Sentinel-2 satellites and other (geo-)datasets can be combined to map nation-wide proxies of material stocks. The candidate will develop a big data concept and methodology on how to extract proxies that relate to material stocks from Copernicus data and other data sources. The data analysis shall be employed in a scalable approach on HPC and/or on cloud platforms. The study shall lead to national maps of anthropogenic material stocks for large areas, including e.g. selected countries in Europe, the USA, China and India. The position will contribute to the European Research Council (ERC) Advanced grant “Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society - MAT_STOCKS”. The postdoctoral researcher will closely collaborate with a doctoral researcher and a team with focus on satellite remote sensing and big data analysis at Humboldt-Universität zu Berlin. For details on the ERC grant, please refer to http://cordis.europa.eu/project/rcn/211243_en.html. For details on the remote sensing science please see https://www.geographie.hu-berlin.de/en/professorships/geomatics/projects/matstocks/mat_stocks.
The successful applicant will join the Geomatics Lab (Prof. Patrick Hostert) at HU Berlin’s Geography Department and will closely collaborate with the Institute of Social Ecology in Vienna (Prof. Helmut Haberl, Prof. Karl-Heinz Erb). The Geomatics Lab’s focus is on advanced remote sensing approaches to gain deeper insights into the state of land systems and related changes of land cover and land use. We collaborate with researchers and science institutions worldwide and are active contributors to leading remote sensing programs, such as the Landsat Science Team (https://landsat.usgs.gov/2018-2023-science-team) and the EnMAP Scientific Advisory Group (http://www.enmap.org/?q=science). Working language of the lab is English.
We offer a position in an international, young and dynamic team with an excellent scientific record. Payment will be according to the local tariff (100% of EG13 in TV-L HU) and includes full social benefits/health insurance. Depending on work experience the annual salary may range from ca. 51,000-66,000 EUR (gross, before taxes and contribution to social insurances). Funding for participation in scientific conferences and relevant workshops is available. HU Berlin is a family-friendly university and seeks to increase the proportion of women in research and teaching, and specifically encourages qualified female scientists/researchers to apply. Applicants with disabilities with equivalent qualifications will be given preferential consideration.
Please refer to
https://www.personalabteilung.hu-berlin.de/stellenausschreibungen/wissenschaftlicher-mitarbeiter-m-w-d-mit-vorauss-vollzeit-e-13-tv-l-hu-drittmittelfinanzierung-befristet-bis-28-02-2021 for the legally binding German version of the job announcement.
Applicants should include (1) a letter of motivation, (2) a full CV, (3) copies of 2 most relevant peer-reviewed publications, (4) a download link for the PhD thesis, and (5) contact details for three references. Please send the application electronically in a single PDF file to Mrs. Dagmar Woerister (firstname.lastname@example.org). Please include the reference number in the content line of your email.
Application deadline: 18th April 2018
For further information please contact Dr. Sebastian van der Linden (email@example.com).
We seek a highly motivated candidate with a PhD related to satellite remote sensing and experience in big data analyses. The methodological focus will be on remote sensing and extend into the domains of geographic information systems and spatial statistics. Proficiency in Python and/or similar programming languages is mandatory. Experience and interest in land systems research is advantageous. We expect excellent command of the English language, good communication skills, and willingness to integrate in an international research team.
EURAXESS offer ID: 292908
The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.
Please contact firstname.lastname@example.org if you wish to download all jobs in XML.