|From||Gabrielle De Lannoy <email@example.com>|
|Cc||"Kim, Edward J. \(GSFC-6170\)" <firstname.lastname@example.org>, Ludovic Brucker <email@example.com>|
|Date||Tue, 26 Sep 2017 12:31:12 +0200|
========== https://icts.kuleuven.be/apps/jobsite/vacatures/54372683We are searching for an enthusiastic postdoctoral researcher with experience in snow modeling, remote sensing observations and data merging to join us in the Belspo SNOPOST project to advance snow estimation, using data collected during the NASA SnowEx campaign. You will be part of the Department of Earth and Environmental Sciences, Division Soil and Water Management, at the KU Leuven (Belgium), leading research on snow remote sensing and modeling. Activities include close collaboration with scientists at NASA Goddard Space Flight Center.
Remote sensing of snow water equivalents has been notoriously difficult, especially in forested areas. NASA has launched a multi-year airborne campaign, SnowEx, to collect a wealth of data over a variety of snow covered regions. The first campaign was held in February 2017 in Grand Mesa, Colorado (US), a flat region with varying forest densities. Airborne remote sensing data were collected using multiple traditional and experimental techniques, including lidar, active microwave, and multi/hyper-spectral visible/infrared imagers. In addition, a variety of terrestrial remote sensing data were collected. During the same period, large groups of scientists intensively sampled snow “on the ground”, and satellite missions looked at Grand Mesa “from space”. Finally, snow can also be simulated over this area using land surface models. The SNOPOST project will optimally combine data from this unique dataset, and collaborate with the SnowEx team, to unlock the potential of remote sensing for snow estimation.
Our team: http://ees.kuleuven.be/bwb/index.html Responsibilities ==========- Perform and disseminate high quality research related to snow remote sensing, land surface modeling, and data merging
- Supervise PhD and/or master thesis students Profile ==========- PhD degree in Hydrology, Civil or Environmental Engineering, Meteorology, Remotely Sensed Earth Observation, Physics, Mathematics, Computer Sciences, or equivalent
- Experience with snow processes, remote sensing and modeling- Experience with statistics, data assimilation or Bayesian merging desirable - Experience with data-processing software such as Matlab/Python, IDL, GrADS, R, or other
- Experience in programming and scientific computing - Excellent motivation and grades - Creative, critical, analytical and innovative mindset - Ability to work independently and lead a small research group- Excellent written and oral communication skills in English, proven in strong publications
Offer ========== - 2-year position with a competitive salary; support in career development - Multi-disciplinary and international professional environment- Leuven is a charming historical university town, located in the heart of Western Europe
Interested? ==========Only scientists matching the above profile should apply. Please submit your resume, along with a motivation letter and two names for references via the online application tool. The start date is 1 January 2018, but can be slightly negotiated. For more information, please contact prof. dr. ir. Gabrielle De Lannoy, tel.: +32 16 37 67 13, e-mail: gabrielle[dot]delannoy[at]kuleuven[dot]be.
Apply for this job no later than 20 November 2017 via the online application tool. The position will remain open until filled by an excellent candidate: http://www.kuleuven.be/eapplyingforjobs/light/54372683
-- ----------------------------------------------------------- Prof. dr. ir. Gabrielle J. M. De Lannoy KULeuven, Department of Earth and Environmental Sciences Division Soil and Water Management Celestijnenlaan 200 E box 2411 B-3001 Heverlee Belgium Rm 02.225 Tel +32 16 37 67 13 http://www.kuleuven.be/wieiswie/en/person/00102378 -----------------------------------------------------------
Go to: Periods · List Information · Index by: Date (or Reverse Date), Thread, Subject or Author.