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Field
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Infrastructure resilience under multi-hazard scenarios Model development and data analyses includes writing well-documented, reusable code (Python or R) Collaborate closely with fellow PhDs and project partners in
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experience of programming (e.g., Python, C#, C++). Ability in teamwork and to work both independently and in groups. English language proficiency. Personal characteristics such as structured approach
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· Programming skills in Matlab, R, and/or Python · Experience in the organisation of field campaigns Language skills · Fluency in English, both oral and written. Your LIST benefits
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other relevant fields. You have programming experience in Python and/or R (e.g. scikit-learn, PyTorch, TensorFlow). You have knowledge of omics technologies, ideally mass spectrometry and chemometrics
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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and image analysis (MATLAB or Python), machine learning techniques, and basic programming/coding will be a plus. Fluency in English is mandatory. Willingness to work in an inter-cultural and
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are looking for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in
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deployment; Knowledge of at least one programming language (such as C, Sage, Matlab, Python); If possible, some experience with cryptography - good knowledge of algebra (including field and ring theories, and
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advantage. - Experience with programming languages (e.g. python, C++) is considered a plus. - A strong team player, with well-developed communication and collaboration skills. - Excellent command of written
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g