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Field
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) Experience with programming languages (ideally Python) Fluent in written and spoken English Very independent and self-motivated way of working but also excellent teamwork skills High motivation to take on
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programming languages for data analysis (e.g., R, Python). Experience with mass spectrometry-based metabolomics approaches, including LC-MS/MS. Experience operating, maintaining, and troubleshooting LC-MS/MS
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to be a merit for the position are both theoretical and practical knowledge of Quantum optimisation, and Quantum Machine Learning and extensive programming experience, e.g., Qiskit, Python, TorchQuantum
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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(for example instruments control) You have proven experience in Python development You have experience in software development and validation, especially complex simulation software Ideally, you have direct
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with proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, Python etc.). You should have a strong vision to evaluate and demonstrate the research findings in
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across large cohorts (e.g., >300 samples) demonstrated experience in data analysis, visualisation, and machine learning, using programming languages such as R or Python excellent interpersonal, verbal, and
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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in complementary methods such as ICP-MS, XRD, XPS, SEM, TEM, EDX Scripting in Matlab, Python or equivalent languages for data analysis Strong publication record in peer-reviewed journals What you will
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for predictivemodelling and large foundation models for earth systems. Skillsetssuch as programming in Python/R, Google Earth Engine, JavaScript, database management environments, Geographical AI, and machine learning