Job Description

I.M. Systems Group, Inc., IMSG, ( a science-based company providing professional scientific and technical support to the Federal government, is leading a Team of prestigious companies to pursue the multi-year service contract to support NASA Goddard Space Flight Center (GSFC) Global Modeling and Assimilation Office (GMAO). We are soliciting qualified candidates to fill multiple global numerical modeling and data assimilation positions including Support Scientists, Scientific Programmer Analysts, Science-Oriented Software Engineers, High Performance Computing (HPC) Software Engineers, Graphics Systems Specialists, and Science Engagement Specialists. The GMAO develops, operates, and maintains comprehensive models and data assimilation systems for the Earth’s atmosphere, ocean, land surface and cryosphere, including atmospheric composition and ocean biogeochemistry. Collectively, these Goddard Earth Observing System (GEOS) models and assimilation systems are configured to support NASA’s Earth Science missions, research activities, and applications, with emphases on research and innovation. GEOS systems also contribute to our nation’s capabilities in climate, weather, and environmental analysis and prediction. The data assimilation systems comprise the assembly, pre-processing, quality control and characterization of all the observations being assimilated, the analysis systems which combine model and observation information, and the Earth system models required to interface with the analysis systems.

GEOS models and assimilation systems are developed using existing software frameworks, such as the Earth System Modeling Framework (ESMF); they are presently transitioning to adopt new data assimilation capabilities using the Joint Effort for Data assimilation Integration (JEDI); they rely heavily on leading-edge high-performance computing platforms. These highly configurable systems are developed and maintained using modern software practices within a complex ecosystem consisting of semi-independent packages, many of which are shared with partner institutions. The GMAO collaborates within NASA and with the external science community in developing and validating its models and data assimilation systems. These positions will support the comprehensive range of GMAO research, development, and production activities.

The vast majority of GMAO activities require extensive expertise in both science and software development.

Ideal candidates will have a suitable education background (e.g., PhD and MS degrees in relevant disciplines) and proven working experience on similar science and systems.

Key Words: Data Assimilation, Global Modeling, Earth System Modeling, NASA, GMAO, JEDI, GEOS

REPONSIBILITIES :

These positions develop and implement advanced coupled models (e.g., ocean-atmosphere-land surface-cryosphere, composition-circulation, ocean dynamics-biology) to support the assimilation systems and to address key scientific questions and prediction goals identified by the NASA Science Mission Directorate.

Specific responsibilities include (but not limited to)

· Atmospheric data assimilation system development and experimentation

· Atmospheric constituent modeling and data assimilation

· Land surface data assimilation

· Ocean data assimilation system development and experimentation

· Couple data assimilation development and experimentation

· Observing system simulation experiments (OSSE)

· Model development and validation of the Earth system model

· Systems integration

· Production of Earth system simulations, analyses, and predictions (on both weather and climate time scales)

· Visualization of observed and model-generated fields of scientific results

· GEOS production operation

· General project support including coordination, planning, training, meetings, reports, etc.

· Research project support to project scientists, including: understanding the strengths and weaknesses of GEOS data products, contributing to the design/implementation/documentation of cloud-resolving OSSE, visualization tools, and ocean modeling and data assimilation; supporting algorithm, modeling, and data assimilation related activities for the Atmospheric Observing System (AOS); exploring various research opportunities to improve GEOS system; supporting scientific computing, modeling analysis and prediction, applied R&D, GEOS and global modeling interface, software engineering, and cloud computing.

REQUIRED/PREFERRED QUALIFICATIONS:

(A subset of the following experience/background/skills):

• MS or PhD degree in Earth system science disciplines (including atmospheric sciences, oceanic science, geophysics, numerical modeling), computing, and other relevant fields. BS degrees in these fields with demonstrated experience will be considered.

• Experience with numerical modeling development for Earth’s atmosphere, ocean, land surface and cryosphere.

• Experience with data assimilation methodology and numerical techniques.

• Advanced knowledge on data thinning techniques to improve the efficiency and effectiveness of data assimilation.

• Experience developing scientific software for use with Earth system models.

• Proficient with scientific programming languages (e.g., FORTRAN, C/C++, Python, etc.), shell scripts, etc.

• Knowledge and experience with the Earth System Modeling Framework (ESMF) or similar modeling system architecture.

• Experience with high performance computing (HPC) environments for scientific computing.

• Knowledge of AI/ML methodology and techniques for data assimilation high preferred.

• Excellent communications and presentation skills.

• Incumbent working experience at NASA GMAO highly preferred.

• U.S. citizenship or green card is required.

Candidates must be a U.S. Citizen or Green Card Holder to qualify

(US Citizen must live in US for 3-5 years prior to application)

(please indicate in your cover letter).

To   Apply

Please apply online at  IM Systems Group, Inc. | Current Opportunities (imsg.com)

IMSG is an Equal Opportunity Employer and Veteran and Disability friendly.

PIdc834ff66b6c-30492-35483242

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