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Field
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technology, also documented experience of technical programming in e.g. Python or Java are a merit. Experience with modelling and simulation in stormwater management are an added advantage. assessed ability
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academic degree (Master's) in computer science, mathematics, data science, computational linguistics, cognitive science or a related discipline Sound programming knowledge in Python and TypeScript/JavaScript
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packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
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. PV field system data analysis (time-series data analysis with JMP software and /or Python). Accelerated ageing procedures (IEC standards). PV module failure modes. Corrosion. Strong communications
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experience with statistical analysis and programming (Bash, R, MATLAB, Python or similar) is required. Excellent communication and collaborative skills (team player) is required. Excellent English scientific
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packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
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) applications in the power grid. • Experience with power system modeling, simulation, dynamics and/or optimization, phasor and electromagnetic transient (EMT)-based modeling, and Python and/or Matlab
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programming (R, Python, or similar) is an advantage. Interest in acquiring the necessary statistical analysis and programming skills is required. Previous experience with experimental research is an advantage
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about to obtain) a PhD in the broad area of Computational Modelling applied to geochemical or biological systems, and be comfortable working routinely in modern programming languages (e.g. Python, Julia
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cell technology. Experience with RNA sequencing, gene editing (CRISPR-Cas9), single particle imaging, and large data set analysis. Proficiency in programming languages like R, python, Matlab Online