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Temporary Research Assistant (Geospatial Data Scientist)

Woodwell Climate Research Center Inc
5.0(1)
AI/ML & Data
Falmouth, MA 02540
1 week ago
🤖 AI-First🛠️ Cursor-friendly🌍 Remote💻 Open Source
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Explicitly requires vibe coding skills (mentions Claude Code) and involves building/fine-tuning GeoAI foundation models for AI-driven time-series forecasting.

About the Role

Temporary Research Assistant (Geospatial Data Scientist) for a 3-month project to implement, train, and validate a proof-of-concept deep learning framework that unifies diverse climate datasets for multi-domain time-series forecasting. The role is the core technical contributor working with the PI and climate scientists and may lead to co-authorship on a publication.

Job Description

Role

Join Woodwell Climate’s Arctic team as a Temporary Research Assistant (Geospatial Data Scientist) on a fixed-term, full-time (90-day) project. You will be the primary technical contributor responsible for implementing, training, and validating a proof-of-concept deep learning framework that translates diverse climate datasets into a unified representation for cross-domain time-series prediction. The role involves close collaboration with the PI and a multidisciplinary team and may lead to a second-author co-authorship on a resulting journal publication.

Key Responsibilities

  • Process raw climate data into AI-ready datasets, including data cleaning, curation, and visualization.
  • Build and manage data pipelines that unify diverse climate datasets (physical model outputs, remote sensing, in-situ flux measurements) into a common token representation for model ingestion.
  • Develop and train AI models for multi-domain time-series forecasting; implement, validate, and document model experiments and results.
  • Contribute to scientific documentation and manuscript writing.
  • Collaborate with the PI and multidisciplinary climate science team throughout model development and evaluation.

Requirements

Must have

  • Experience in machine learning and deep learning for time-series forecasting.
  • Experience with multi-domain deep learning approaches.
  • Familiarity with geospatial datasets and geospatial data processing.
  • Experience with Claude Code and vibe coding.

Preferred

  • Experience with climate or Earth science data.
  • Experience fine-tuning GeoAI (geospatial AI) foundation models.

Qualifications

  • Master’s in Computer Science, Data Science, Environmental Science, or a related quantitative field; or a Bachelor’s degree plus 2 years of professional experience.

Logistics

  • Term: Fixed-term, 90 days (full-time, typically 40 hours/week, Monday–Friday).
  • Classification: Hourly, non-exempt; hourly rate stated as $17/hour (dependent on qualifications/experience).
  • Location: Falmouth, Massachusetts — onsite, hybrid, or remote options noted.
  • Desired start date: March 31, 2026.

Tech Stack

Claude CodeGeoAIGeoAI foundation modelsDeep learningMachine learningTime series forecasting

Skills

Machine LearningDeep LearningTime Series ForecastingMulti-domain ModelingGeospatial Data ProcessingData CleaningData CurationData VisualizationData Pipeline DevelopmentModel Training and ValidationScientific WritingCollaborationVibe Coding

Experience Level

Mid

Salary

USD 17+/year

Employment Type

TemporaryFull-time

Benefits

  • Full-time (40 hours/week)
  • Hourly pay ($17/hour)
  • Fixed-term (90 days)
  • Non-exempt (hourly)
  • Onsite, hybrid, or remote location options
  • Potential co-authorship on resulting publication