CISL Scientist III (Ocean Data Assimilation)

University Corporation for Atmospheric Research•Boulder, CO

35d•Hybrid

About The Position

CISL advances Earth system science research by providing scientists with large-scale computing capabilities, access to datasets, and innovative analysis tools. CISL scientists engage in computational science, data assimilation, and machine learning research to enhance understanding of our planet. CISL supports thousands of researchers annually and fosters the next generation of scientists and cyberinfrastructure professionals through our educational programs. CISL operates Derecho, one of the world's most powerful supercomputers dedicated to open Earth science research, and a comprehensive ecosystem of computing and data resources. Derecho and the rest of NSF NCAR's integrated research computing and data environments are housed at the NSF NCAR-Wyoming Supercomputing Center (NWSC) in Cheyenne, Wyoming. The Project Scientist will join the Data Assimilation Research Section (DAReS) in the Computational and Information Systems Laboratory (CISL); a dynamic, collaborative team advancing the science and technology of data assimilation (DA) for Earth system research. CISL provides high-performance computing, data services, and software engineering to support the atmospheric and related sciences community. DAReS develops and maintains the Data Assimilation Research Testbed (DART), an open-source, community software framework for ensemble DA. Our mission is to enable scientists to easily integrate observations with numerical models to improve prediction. This role will focus on: Developing, enhancing and supporting DA activities using DART Exploring AI tools for enhancing efficiency, accuracy, and diagnostics of the DA framework Leading and contributing to proposals, peer-reviewed publications, and community engagement Building strong collaborations within NSF NCAR and with national/international partners Conduct quality collaborative research on scientific topics such as: Support ocean DA activities across many models such as MOM6, ROMS, MITgcm, etc Integrating new observation types (e.g., satellite remote sensing, in-situ networks) into DART Implementation and evaluation of newly developed algorithms in DART Enhanced diagnostic tools for DA research Develop and evaluate AI/ML approaches for DA, such as: ML-based observation operators, bias correction, or model error estimation Surrogate modeling to reduce DA computational costs Advanced diagnostics using pattern recognition or anomaly detection Lead and contribute to funding proposals. Serve and PI or co-PI on funded projects. Mentor students and early-career scientists in DA and AI-related applications. Support activities of the DAReS team by guiding software development and documentation. Share research outcomes via publications, presentations, workshops, and training sessions. Designs and executes scientific analyses; develops, and adapts, and/or tests hypotheses, models and/or tools. Contributes to papers, reports, technical documentation, data sets, findings, and/or proposals. Mentors less experienced colleagues, collaborates across disciplines, and supports proposal development to advance scientific goals through high-quality, methodologically sound work. Engages in mission-aligned activities both within the organization and throughout the broader scientific community. Contributes through a combination of scientific expertise, professional service, and education and outreach efforts.

Requirements

Ph.D. in atmospheric science, oceanography, hydrology, applied mathematics, computer science, or a related field, or an equivalent combination of education and experience.
Has solid knowledge in a relevant scientific field, with an ability to apply theories, methods, or frameworks to complex or interdisciplinary problems.
Is familiar with project planning and proposal development, including scoping technical work, aligning with program goals, and supporting deliverable management.
Is skilled in developing or refining scientific tools, workflows, or models, including quality assurance and integration with broader project efforts.
Is skilled in using data analysis tools used for data preparation, visualization, or workflow automation.
Is committed to mentoring with the ability to guide less experienced colleagues on methods, tools, and collaborative practices.
Is capable of contributing to peer-reviewed publications, sponsor reports, or presentations, with clear and accurate scientific communication tailored to varied audiences.
Collaborates effectively within multidisciplinary teams, integrating diverse inputs and fostering productive working relationships.
Demonstrates the ability to design and carry out analyses or investigative tasks independently using established methods, adapting approaches as needed.
Demonstrated experience with ensemble/variational DA and its application to Earth system models
Experience developing and applying AI/ML techniques in scientific modeling or data analysis
Strong record or peer-reviewed publications and conference presentations
Proficiency in scientific programming (Fortran, Python, and scripting languages)
Effective communication skills for technical and diverse audiences
Proven ability to collaborate effectively and work in multidisciplinary, culturally diverse teams

Nice To Haves

Experience with DART and NSF NCAR community models (CESM, MOM6, WRF-Hydro, MPAS)
Knowledge of software engineering best practices (Git/GitHub workflows, documentation)
Experience integrating new observation types into DA systems
Track record in proposal development and project leadership

Responsibilities

Designing and executing scientific investigations or analyses using established and/or emerging methods to address defined research, operational, or applied science questions.
Developing or adapting tools, models, or methods to support data collection, processing, analysis, system evaluation, or experimental workflows.
Performing detailed analysis and interpretation of observational, experimental, or model-generated data, contributing to new insights or improvements in scientific understanding.
Leading or contributing to components of a larger project or small project teams through coordination of activities, deliverables, and technical direction across collaborators.
Authoring or co-authoring peer-reviewed publications, technical documentation, data sets, findings, project reports, and/or proposals, and presenting findings in internal, sponsor, or scientific community settings.
Collaborating across disciplines and institutions, contributing technical expertise to team-based projects and enhancing interdisciplinary research or operational outcomes.
Supporting proposal development and project planning activities by contributing to scoping, technical writing, and alignment with programmatic objectives.
Providing technical guidance to less experienced staff/students, mentoring on methods, tools, and best practices while engaging in and modeling inclusive team participation.
Developing products, tools, instruments and/or technologies for projects and programs.

Benefits

Tuition Assistance, time off allowance to attend classes, and other professional development opportunities.
UCAR contributes 10% of your eligible pay into your retirement account; 100% fully vested on day one.
Starting minimum accrual of 20 days of personal time off each year (prorated for less than full-time positions).
10 paid holidays.
12 weeks of paid parental leave.
Short-term medical leave paid at 100% of your regular salary.
EcoPass for local Colorado residents to use the Denver and Boulder-area transit system at no cost.

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