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Remote Computational Modeling Jobs in California

... computational cost, and transferability. * Capture Dynamic Earth Events: Design embeddings and ... remote sensing and satellite image analysis, with a proven track record in building AI-based models ...

CFD Engineer

Mojave, CA ยท On-site +1

To support these efforts, Stratolaunch is seeking a Computational Fluid Dynamics (CFD) Engineer ... Analyze wind tunnel and flight test data as required to validate CFD models * Develop and maintain ...

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and ... computational biologists, and software engineers to translate complex research needs into high ...

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

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Remote Computational Modeling information

What are the key skills and qualifications needed to thrive as a Remote Computational Modeling Specialist, and why are they important?

To excel in Remote Computational Modeling, you need a strong background in mathematics, physics, and computer science, often supported by a relevant degree such as in engineering or applied sciences. Proficiency with modeling software (like MATLAB, ANSYS, or COMSOL), programming languages (such as Python or C++), and cloud computing platforms is typically required. Outstanding analytical thinking, problem-solving abilities, and effective remote communication skills set top candidates apart. These competencies ensure accurate model development, efficient collaboration, and the ability to deliver reliable results in a remote work environment.

What is remote computational modeling?

Remote computational modeling is the process of creating and simulating mathematical models of real-world systems using computer software, performed from a location outside a traditional office or laboratory setting. Professionals in this field use specialized software to analyze complex data, make predictions, and solve scientific or engineering problems, all while collaborating virtually with teams or clients. This remote setup allows for greater flexibility and access to global projects, making it an attractive option for computational scientists, engineers, and analysts.

What is the difference between Remote Computational Modeling vs Remote Data Analysis?

AspectRemote Computational ModelingRemote Data Analysis
Required CredentialsDegree in computational science, engineering, or related fields; programming skillsDegree in statistics, data science, or related fields; analytical skills
Work EnvironmentCollaborative teams, research labs, or industry projects involving simulationsData-focused environments, business analytics, or research settings
Industry UsageEngineering, scientific research, product developmentBusiness, marketing, healthcare, finance
Search & Comparison IntentUnderstanding roles involving simulation and modeling techniquesAnalyzing data sets to derive insights

Remote Computational Modeling involves creating simulations and models to predict or analyze complex systems, often requiring programming and scientific expertise. Remote Data Analysis focuses on examining data sets to extract meaningful insights, typically using statistical tools. While both roles require analytical skills and often overlap in technical knowledge, they serve different purposes within industries like engineering, research, and business.

What are some common challenges faced by professionals in remote computational modeling roles, and how can they be addressed?

Professionals in remote computational modeling often face challenges such as maintaining effective communication with team members, managing complex simulations across distributed systems, and staying aligned with project goals without in-person oversight. To overcome these obstacles, it's important to leverage collaboration tools, establish regular check-ins with your team, and document your work thoroughly. Additionally, setting up a reliable remote work environment with necessary software and high-speed internet can help ensure productivity and minimize technical disruptions.
What are the most commonly searched types of Computational Modeling jobs in California? The most popular types of Computational Modeling jobs in California are:
What are popular job titles related to Remote Computational Modeling jobs in California? For Remote Computational Modeling jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Remote Computational Modeling jobs? Cities in California with the most Remote Computational Modeling job openings:
Visiting Staff Scientist

Visiting Staff Scientist

Planet

San Francisco, CA โ€ข On-site, Remote

Other

Medical, Dental, Vision, PTO

Posted 15 days ago


Job description

About the Role:

We are seeking a distinguished Visiting Staff Scientist to join our AI Research (AIR) team for a one-year sabbatical residency. In this role, you will play a pivotal part in our mission to create a "Queryable Earth" by leading the development of Planet's proprietary geospatial foundation models (GFMs).

While Planet has historically leveraged external models like Google's RSFM and RemoteCLIP, we are now focused on building in-house models specifically trained on our unique imagery. You will lead research into creating temporally dense embeddings that go beyond static annual summaries, capturing the dynamic and ephemeral nature of our planet-from rapid flooding to disaster impacts.

You will collaborate with a multi-disciplinary team of "Planeteers" across space operations, data pipelines, and analytics to co-develop AI/ML solutions that leverage the high spatial resolution and near-daily revisit of PlanetScope data.

Impact You'll Own:

  • Develop Planet's Proprietary GFM: Lead the research and development of a foundation model specifically trained on Planet imagery, incorporating the time-axis to create high-cadence time-series embeddings.
  • Benchmark Geospatial Architectures: Systematically evaluate and compare existing GFMs (e.g., TerraMind, Prithvi, Clay) against PlanetScope data to assess performance, computational cost, and transferability.
  • Capture Dynamic Earth Events: Design embeddings and workflows optimized for detecting short-lived, high-impact events such as floods, rapid surface-water expansion, and fire.
  • Multi-Sensor Integration: Explore the synergy between PlanetScope, Sentinel-1 SAR, and other commercial SAR data to ensure robust time-series analysis even under cloud cover.
  • Human-in-the-Loop Innovation: Use embeddings to design active learning workflows that prioritize labeling and reduce the annotation burden for time-sensitive mapping tasks.
  • Academic & Technical Leadership: Publish findings in top-tier journals and present at conferences (e.g., IGARSS, CVPR), highlighting PlanetScope's unique value in the foundation model ecosystem.
  • Mentor & Collaborate: Oversee the technical direction of a dedicated postdoc and collaborate with Planet's research scientists to transition prototypes into operational products.

What You Bring:

  • Distinguished Academic Background: PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field.
  • Deep Domain Expertise: 12+ years of experience in remote sensing and satellite image analysis, with a proven track record in building AI-based models for environmental change (e.g., flood-extent, water dynamics).
  • Multimodal AI Fluency: Extensive experience with foundation models, contrastive learning (CLIP-like models), and multi-model vision-language models (MMVLMs).
  • Advanced Geospatial Toolkit: Proficiency in multi-sensor integration (Landsat, Sentinel-2, PlanetScope, Sentinel-1) and high-resolution mapping at varying scales (3m, 10m, 30m).
  • Technical Proficiency: Expert-level Python skills and experience with the scientific stack (xarray, Dask, NumPy, Rasterio, GeoPandas) and deep learning frameworks.
  • Scale-Minded Research: Experience building automated pipelines for preprocessing and labeling planetary-scale datasets.
  • Collaborative Spirit: A history of leading research labs and a desire to work in a fast-paced, industrial R&D environment.

What Makes You Stand Out:

  • Specialized Environmental Research: Extensive experience specifically in flood damage quantification and methane-related water dynamics.
  • Proven Funding & Publication Record: History of leading NASA-funded or similar high-impact geospatial research projects.
  • Architectural Knowledge: Direct experience fine-tuning or modifying specific GFM architectures like TerraMind or Prithvi.

Hybrid Experience: A mix of deep academic rigor and the ability to prototype rapid-change monitoring tools for operational readiness.

Application Deadline:

August 11, 2026 by 11:59p / 23:59 CET (Central European Time)

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

  • Comprehensive Medical, Dental, and Vision plans
  • Health Savings Account (HSA) with a company contribution
  • Generous Paid Time Off in addition to holidays and company-wide days offย 
  • 16 Weeks of Paid Parental Leave
  • Wellness Program and Employee Assistance Program (EAP)
  • Home Office Reimbursement
  • Monthly Phone and Internet Reimbursement
  • Tuition Reimbursement and access to LinkedIn Learning
  • Equity
  • Commuter Benefits (if local to an office)
  • Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below. Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location. The range displays our typical hiring range for new hire salaries in US locations only. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.