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Field
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Applications are invited for a Postdoctoral researcher in convection and aerosol research with satellite based remote sensing. This position, part of the EU Horizon Europe project Clouds and climate
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud
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- Conference travel support - 1-year contract, renewable (up to 3 years total) - Cloud compute provided by Nebius Requirements: - PhD in Mathematics or Computer Science - For existing projects: willingness
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analysis. Familiarity with bioinformatics software (e.g., R, Python, GSEA, PRISM, CellProfiler) and cloud‑based data platforms. Strong written and oral communication skills; ability to lead interdisciplinary
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 months ago
surface, aerosols, clouds, and climate change. In-house capabilities include design and development of novel airborne instruments for aerosol, cloud and trace gases systems. For the past year, we hosted a
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the job posting. Work Experience: No additional work experience unless stated elsewhere in the job posting. Skills: Adobe Creative Cloud, Analytical Thinking, Audience Engagement, Curriculum Development
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), Transformer-based modeling, and clinical NLP is highly desirable. Experience with cloud platforms such as Google Cloud Platform (GCP) or Microsoft Azure, and tools like BigQuery, Vertex AI, or Azure ML Studio
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development and web-based applications, back-end services and API design (e.g., FastAPI, Flask), and deploying applications in local or cloud environments. Experience working with large-scale datasets
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required