[unav_all] Geodesy/geophysics postdoc vacancies at JPL

David Bekaert bekaertdavid at gmail.com
Thu May 18 08:07:10 MDT 2017


Dear Colleagues,


We are seeking interested applicants for two postdoc positions at the Jet
Propulsion Laboratory working on utilizing geodetic data from InSAR and GPS
for tectonic modeling and subsidence. Candidates should be working towards
a PhD degree or have a PhD. Please find details below.



*1.     **Caltech postdoc at JPL:*

*Title:* Utilizing geodetic data for time-dependent modeling of slow slip
events along the Mexican subduction Zone



The proposed research aims at time-dependent modeling of geodetic data to
map slow slip. Candidates should have a recent PhD in geodesy, earth
science, engineering or a related field. Candidates should also have good
programming experience in Matlab and Python. C++ is considered an
advantage. Prior experience in either large-scale time-series InSAR
processing (e.g., GIAnT or StaMPS), InSAR ionospheric/tropospheric noise
corrections (e.g., PyAPS, TRAIN, or split spectrum ionospheric
corrections), integration of GNSS and InSAR datasets, or inverse modeling
of long-wavelength tectonic processes such as interseismic deformation,
creep, and slow slip is strongly recommended.



*Details:* https://postdocs-jpl.icims.com/jobs/8378/utilizing-
geodetic-data-for-time-dependent-modeling-of-slow-
slip-events-along-the-mexican-subduction-zone/job?mode=view







*2.     **NPP postdoc at JPL:*

*Title*: Mapping subsidence of urban areas and critical infrastructure
along the US East Coast using time-series InSAR analysis



The proposed research aims to resolve the gaps in our current state of
knowledge, by combining GPS with available satellite SAR data (TerrarSAR-X,
Cosmo-SkyMed, Sentinel-1A/B etc.) to produce the high-spatial resolution,
high accuracy, subsidence maps of urban and critical infrastructure.
Candidates should have a recent PhD in geodesy, earth science, engineering
or a related field. Candidates should also have good programming experience
in Matlab and Python. C++ is considered an advantage. The candidate is
envisioned to use state of the art time-series InSAR processing methods to
extract high resolution subsidence rates, develop and apply methodologies
to quantify the uncertainties, and further integrate observations with GPS
measurements.


*Details*: https://npp.usra.edu/opportunities/details/?ro=19096
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