Climate Hazard Center - Assistant Project Scientist in the Geography Department

The Climate Hazards Center (CHC) at the University of California, Santa Barbara, seeks a highly motivated assistant project scientist.

The Assistant Project Scientist will work with CHC data developers to build extensive and rapidly-updated archives of key weather observations; develop procedures for quality controlling these data archives; develop procedures for blending and interpolating in situ observations with remotely sensed estimates; collaborate with the team to develop improved and expanded gridded temperature, humidity, humid heat, and precipitation archives, along with interoperable weather and climate forecasts; conduct additional modeling, which could include impact models focused on crop water requirements and vegetative health; assist in the development and maintenance of UNIX-based systems for automatic data ingest, processing, modeling, data output, and mapping; and make substantial scientific and scholarly contributions to the CHC's research efforts, especially in regards to accuracy and skill of dataset estimates.

Key responsibilities include:

• Develop and maintain extensive, rapidly updated archives of weather observations and forecasts.
• Design and implement procedures for quality control, validation, blending, and interpolation of in situ weather observations.
• Collaborate with the CHC team to develop improved and expanded gridded archives of temperature, humidity, humid heat, and precipitation, as well as interoperable weather and climate forecast products.
• Support the ingest, validation, interpolation, and analysis of weather data obtained from automated 3D Printed Automatic Weather Stations (3D-PAWS).
• Conduct additional modeling and analysis, including impact models focused on crop water requirements and vegetative health.
• Provide figures, analysis, and written reporting of climate indicators during cropping seasons in food-insecure regions to support early identification of weather- and climate-related risks to crop production and food security.
• Assist in the development and maintenance of UNIX-based systems for automated data ingest, processing, modeling, data output, and mapping.
• Serve as a liaison between the CHC and the campus/department IT group (GRIT) to identify, communicate, and facilitate solutions to issues with the group's compute environment.
• Contribute substantially to CHC’s scientific mission through scholarly research, publications, and operational products.

Applicants must have completed (at least) all requirements for a PhD (or international equivalent) in Atmospheric Sciences, Climate Science, Geography/Remote Sensing, Hydrology, Environmental Science, Earth Science, or a related discipline, except the dissertation, at the time of application.

• PhD in climate science, atmospheric science, hydrology, geography, environmental science, or a closely related field awarded by the time of appointment.

• 4-5 years of experience working with precipitation datasets, seasonal forecast data, water balance models, vegetation/greenness datasets, and other large-scale climate or environmental data products.

• Record of peer-reviewed publications , including leading or significantly contributing to scientific manuscripts

• Minimum 2 years experience harmonizing multi-platform satellite datasets to create consistent, long-term time series products.

• 2-4 years experience developing, maintaining, and operating automated data processing systems in UNIX-based research computing environments, including data ingest, processing, modeling, mapping, and data dissemination.

• 1 year of experience developing, documenting, and operationalizing climate or environmental data products for research or monitoring applications

• 1-3 years of experience managing and processing large geospatial and climate datasets.

• 1-3 years of experience with crop modeling using gridded datasets

• Strong programming skills in scientific computing languages (e.g., Python, IDL, R, MATLAB, or similar), with the ability to work across both legacy and modern codebases.

• Strong background in statistical analysis and model evaluation, including validation of gridded datasets.

• Experience in geostatistical modeling, machine learning, or data-driven prediction methods applied to environmental datasets.

• Experience building and maintaining large, frequently updated archives of weather or climate observations.

• Experience contributing to externally funded research projects.

• Demonstrated interest and experience in applied climate science.

• Strong interpersonal and communication skills to support effective collaboration with colleagues, stakeholders, and external partners.

• Experience managing and processing large geospatial and climate datasets

• Curriculum Vitae - Your most recently updated C.V.

• Cover Letter

• Statement of Research

• 1-3 required (contact information only)

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• “Misconduct” means any violation of the policies or laws governing conduct at the applicant’s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy for Employees, students and third parties
• APM - 035: Affirmative Action and Nondiscrimination in Employment

Additionally, you will be required to comply with the University of California Policy on Vaccination Programs, as may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements.

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.