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Postdoctoral Research Associate in Glaciology and Ice Sheet Modeling
Oak Ridge
Oopsie, you're a wee bit late! The job is closed, hence no longer open for fresh applications.
Position Type Compensation
Full Time, Contract Not Specified
Key Skills Industry
climate change, research, postdoc, hpc, computation Gov & Military

The Computer Science and Mathematics Division in the Computing and

Computational Sciences Directorate and the Climate Change Science Institute (http://climatechangescience.ornl.gov/) at the Oak Ridge National Laboratory

(ORNL) seeks to hire a Postdoctoral Research Associate in Glaciology.


Major Duties/Responsibilities:

The successful candidate will work with a highly diverse team of ice sheet model developers and analysts along with climate, computational, and computer scientists at ORNL, other DOE Labs, and collaborating universities to create a quantitative ice sheet model verification and validation framework. The framework will be designed to support robust ice sheet model development, to enable the comparison of ice sheet model output and observations, and to further understanding of the quality and capabilities of state-of-the-art continental ice sheet models coupled to global Earth system models. The candidate will use a range of tools and methods to quantitatively assess the performance of the Community Ice Sheet Model against observations and other models.


The qualified candidate will:

·       Design and develop new tools for analysis and integration of current and new in-situ and remotely-sensed observational data and model results.

·       Explore new methods and analysis techniques for identifying model biases.

·       Contribute to on going efforts in ice sheet model optimization, initialization, and uncertainty quantification.

·       Contribute to large-scale stand alone and coupled ice sheet model simulations aimed at exploring the potential for future sea level rise from ice sheets

·       Conduct research and report results in open literature journals, technical reports, and at relevant conferences.



·       A Ph.D. in an Earth or environmental science, computer science, or applied mathematics with experience in statistics or uncertainty methods is required.

·       Excellent interpersonal skills are necessary for working within a highly diverse team, as well as strong oral and written communications skills, good organizational skills,and a high degree of personal motivation.

·       A proven publication track record is required.


Preferred Qualifications:

·       Experience with large-scale geophysical model development and analysis and/or a background in working with large-scale glaciological/geophysical data sets is strongly desired.

·       Proven analytical skills using R, Python, and/or similar, and experience with large-scale data analytics are desired.

·       Experience with standard scientific programming languages (C/C++, Fortran), parallel programming and algorithm development is also desired. 


Applicants cannot have received the most recent degree more than five years prior to the date of application and must complete all degree requirements before starting their appointment. Certain exceptions may be considered.


This position is a temporary, full-time assignment not to exceed 24 months.

About Oak Ridge National Laboratory

Oak Ridge National Laboratory (ORNL) is the leader in computing and computational sciences and will continue to ensure that its expertise, resources, and scientific capabilities will remain world class, by recruiting and retaining superior talent.

ORNL is home to Titan, a Cray XK7 system consisting of 18,688 AMD sixteen-core Opteron™ processors providing a peak performance of more than 3.3 petaflops (PF) and 600 terabytes (TB) of memory. A total of 512 service input/output (I/O) nodes provide access to the 10 petabytes (PB) “Spider” Lustre parallel file system at more than 240 gigabytes (GB/s). External login nodes (decoupled from the XK7 system) provide a powerful compilation and interactive environment using dual-socket, twelve-core AMD Opteron processors and 256 GB of memory. Each of the 18,688 Titan compute nodes is paired with an NVIDIA Kepler graphics processing unit (GPU) designed to accelerate calculations. With a peak performance per Kepler accelerator of more than 1TF, the aggregate performance of Titan exceeds 20PF.
Titan is the Department of Energy’s most powerful open science computer system available to the international science community.

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