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, Environmental Science, Remote Sensing, or related field Experience in atmospheric modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record Where to apply
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related to scientific computing - A solid background in multi-linear abler and tensor contractions software development - Proficiency in multiple programming languages (Python, C/C++, or Fortran), ideally
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statistical and geospatial analyses (e.g., using ArcGIS, SPSS, Stata, Python, R). Conduct cross-city comparative research Map and analyse the geographical distribution of eviction patterns within and across
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Vector, Vue.js 3, Node.js, Python, and JSON; Natural Language Processing (NLP) applied to collections; implementation of data pipelines using AI models, embeddings (RAG), and OCR; demonstrated knowledge in
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
. Computer programming in languages such as Python. Oral and written communication skills, including scientific and technical writing, experience writing scientific proposals. Collaboration and team-building
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Research FieldHistory » History of scienceYears of Research Experience1 - 4 Additional Information Eligibility criteria -- Knowledge in fine-scale, high-frequency ocean dynamics - Proficient in Python
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platforms and our local CPU and GPU clusters; implementing Python tools for automating CSP/DFT calculations; - Participation in the scientific activities of the Applied Quantum Chemistry group (IC2MP) and the
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Science, or a related field. Demonstrated experience in image or signal processing, instrumentation data pipelines, or similar. Strong programming skills in Python, R, or MATLAB. Experience with statistical
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opportunities to publish high-impact research addressing forest resilience, disturbance regimes, and climate change. The appointee may work on one or multiple additional ongoing lab projects, depending upon
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prosperous global future depends on the ability to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities