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Field
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exchanged between land, ocean and atmosphere through processes known as global biogeochemical cycles. Research activities in the IMPRS-gBGC aim at a fundamental understanding of these cycles, how
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climatic and land-surface conditions. Contribute to hybrid model components that combine data-driven methods with hydrologic process representations. Improve model generalizability across climatic regimes
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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engineering Willingness to work in laboratory and cleanroom environments Ideally, initial experience in a technical or scientific environment (e.g. cleanroom, laboratory) Knowledge of solid state physics and/or
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realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https
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important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https://go.fzj.de/womens-job
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, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills Excellent cooperation and communication skills
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important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https://go.fzj.de/womens-job
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Helmholtz-Zentrum Berlin für Materialien und Energie | Berlin, Berlin | Germany | about 2 months ago
13 Nov 2025 Job Information Organisation/Company Helmholtz-Zentrum Berlin für Materialien und Energie Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good