Maren Boese
2018-01-15 16:32:04
The *French Institute of Science and Technology for Transport, Development
and Networks* (*Institut français des sciences et technologies des
transports, de l'aménagement et des réseaux*, *IFSTTAR*) and the *Swiss
Seismological Service (SED)* at the ETH Zurich are seeking a highly
motivated postdoc candidate to work on integrating fault properties into
earthquake early warning (EEW). The planned research will be conducted
within the FAULTS_R_GEMS (Properties of FAULTS, a key to Realistic Generic
Earthquake Modeling and hazard Simulation) project, in which we, as a
multidisciplinary and international team of different institutions, seek to
better understand the interactions between seismic faults and earthquakes. The
postdoc will be employed and based at IFSTTAR Paris (France), but is
expected to frequently visit ETH Zurich (Switzerland) for extended research
stays.
*IFSTTAR *(http://www.ifsttar.fr/) is a French institute involved in
science and technology for transport, urban planning and networks. In
particular, The "Earthquakes and Vibrations" Lab investigates seismic
phenomena as well as vibrations: seismic hazard, propagation and
amplification of seismic waves in complex geological structures, vibrations
in soils and structures, dynamic soil-structure interaction, dynamic
behavior of structures and foundations, vulnerability, risk assessment. Our
researchers mainly develop physical, mechanical and numerical models
associated to observations in the lab and on the field.
The *SED* (http://www.seismo.ethz.ch) is a leading European seismological
research, education and service agency; it is responsible for national
seismic monitoring and operates the Swiss national broadband, short-period
and strong-motion networks. The SED is one of the globally recognized
leaders in the domain of rapid earthquake characterization, including EEW.
EEW algorithms developed in our team include point-source approaches such
as the Virtual Seismologist and Gutenberg Algorithm, and the finite-source
FinDer algorithm. Some of these methods have been integrated into the
open-source and widely used SeisComP3 seismic monitoring software, and are
running in real-time in Switzerland, California, Central America, and Chile.
*We are looking for* a researcher that will explore and develop
methodologies for the optimum use of prior knowledge of fault properties,
expected rupture evolution, and ground-motions for EEW. Goal is the
development of a “Prior EEW module” to enhance probabilistic estimates from
our current Bayesian-based EEW system.
The primary responsibilities for the researcher are:
· Incorporate expected rupture evolution into EEW
· Determine and integrate fault-specific prior probabilities into EEW
· Perform real-time and offline tests of the new “Prior EEW module”
as part of our existing EEW platform
· Collaborate and meet with other FAULTS_R_GEMS partners
The position is initially for 24 months, with the possibility of extension.
Regular travel to ETH Zurich is expected. The working language at IFSTTAR
and SED is English, yet some notions of French would be useful. Targeted
start date of the position is May 2018. The selection process starts
immediately (January 2018) and will continue until the position is filled.
*The candidate should have* a PhD in geoscience, engineering or a related
field with documented experience on relevant subjects, which may include
earthquake early warning, software development for seismic networks, and
earthquake statistics. A solid background in programming, preferably in
Python or Matlab, is required. Postdoctoral experience and / or familiarity
with SeisComP3 are not necessary, but would be of advantage.
*We are looking forward to* your application including a CV, a statement of
research interests, and the names and complete contact information of three
referees. Only complete applications will be considered.
*For further information and application** submission,* contact Dr. F.
Bonilla and Dr. M. Böse by email: fabian.bonilla<at>ifsttar.fr,
maren.boese<at>sed.ethz.ch <maren.boese<at>sed.ethz.ch>.
*Closing date:* April 30, 2018.
and Networks* (*Institut français des sciences et technologies des
transports, de l'aménagement et des réseaux*, *IFSTTAR*) and the *Swiss
Seismological Service (SED)* at the ETH Zurich are seeking a highly
motivated postdoc candidate to work on integrating fault properties into
earthquake early warning (EEW). The planned research will be conducted
within the FAULTS_R_GEMS (Properties of FAULTS, a key to Realistic Generic
Earthquake Modeling and hazard Simulation) project, in which we, as a
multidisciplinary and international team of different institutions, seek to
better understand the interactions between seismic faults and earthquakes. The
postdoc will be employed and based at IFSTTAR Paris (France), but is
expected to frequently visit ETH Zurich (Switzerland) for extended research
stays.
*IFSTTAR *(http://www.ifsttar.fr/) is a French institute involved in
science and technology for transport, urban planning and networks. In
particular, The "Earthquakes and Vibrations" Lab investigates seismic
phenomena as well as vibrations: seismic hazard, propagation and
amplification of seismic waves in complex geological structures, vibrations
in soils and structures, dynamic soil-structure interaction, dynamic
behavior of structures and foundations, vulnerability, risk assessment. Our
researchers mainly develop physical, mechanical and numerical models
associated to observations in the lab and on the field.
The *SED* (http://www.seismo.ethz.ch) is a leading European seismological
research, education and service agency; it is responsible for national
seismic monitoring and operates the Swiss national broadband, short-period
and strong-motion networks. The SED is one of the globally recognized
leaders in the domain of rapid earthquake characterization, including EEW.
EEW algorithms developed in our team include point-source approaches such
as the Virtual Seismologist and Gutenberg Algorithm, and the finite-source
FinDer algorithm. Some of these methods have been integrated into the
open-source and widely used SeisComP3 seismic monitoring software, and are
running in real-time in Switzerland, California, Central America, and Chile.
*We are looking for* a researcher that will explore and develop
methodologies for the optimum use of prior knowledge of fault properties,
expected rupture evolution, and ground-motions for EEW. Goal is the
development of a “Prior EEW module” to enhance probabilistic estimates from
our current Bayesian-based EEW system.
The primary responsibilities for the researcher are:
· Incorporate expected rupture evolution into EEW
· Determine and integrate fault-specific prior probabilities into EEW
· Perform real-time and offline tests of the new “Prior EEW module”
as part of our existing EEW platform
· Collaborate and meet with other FAULTS_R_GEMS partners
The position is initially for 24 months, with the possibility of extension.
Regular travel to ETH Zurich is expected. The working language at IFSTTAR
and SED is English, yet some notions of French would be useful. Targeted
start date of the position is May 2018. The selection process starts
immediately (January 2018) and will continue until the position is filled.
*The candidate should have* a PhD in geoscience, engineering or a related
field with documented experience on relevant subjects, which may include
earthquake early warning, software development for seismic networks, and
earthquake statistics. A solid background in programming, preferably in
Python or Matlab, is required. Postdoctoral experience and / or familiarity
with SeisComP3 are not necessary, but would be of advantage.
*We are looking forward to* your application including a CV, a statement of
research interests, and the names and complete contact information of three
referees. Only complete applications will be considered.
*For further information and application** submission,* contact Dr. F.
Bonilla and Dr. M. Böse by email: fabian.bonilla<at>ifsttar.fr,
maren.boese<at>sed.ethz.ch <maren.boese<at>sed.ethz.ch>.
*Closing date:* April 30, 2018.
