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: The position is embedded at Forschungszentrum Jülich (FZJ), one of Europe’s largest interdisciplinary research centers, offering access to world-class computational resources (HPC), state-of-the-art research
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Orchestration Services Familiarity with HPC Cluster Administration and CI/CD tools (Azure DevOps) Experience with Amazon Web Services, Microsoft Azure, or Google Cloud Platform (AWS CloudFormation or Azure
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AI, or active learning for materials applications. Integration of theory and experiment: Using computation and ML to interpret or guide experimental work. High-performance computing (HPC) and data
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, thermodynamics, modelling; and/or ML/AI, data science, statistics, image analysis, scientific programming (Python/R/Julia), HPC; Strong motivation for interdisciplinary research and international collaboration
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
solution-oriented environment Salary according to the usual hourly rates for student/ scientific assistants in Brandenburg Access to HPC Flexible working hours Possibility of remote work a collegial and open
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ML to interpret or guide experimental work. High-performance computing (HPC) and data management for large-scale materials datasets. KEY SELECTION CRITERIA Join us if you have: Doctorate degree from a
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postdoctoral position is available in the ultrafast science theory group of Prof. Lun Yue (https://sites.google.com/binghamton.edu/yue/ ) at Binghamton University (State University of New York). The successful
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) System Administration, coding (Python, Bash, SQL, etc.), virtualization, large-scale storage systems, HPC, lab machine administration, web server administration, procurement, research computing
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biology approaches and early-adoption of cutting-edge technologies Operating with Linux and high-performance clusters (HPC) R/Python and Snakemake or Nextflow (or comparable platforms) OUR REFERENCES
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workflows. Familiarity with Linux/HPC environments (for the modeling position). Experience with data visualization or handling large datasets. Demonstrated interest in climate physics and/or cross