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-time programming (C++, Python) Knowledge of the following is a plus: Real-time communication systems (e.g. EtherCAT, CAN bus) Closed-loop control of robotic systems Experience with experimental human
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environmental datasets; proficiency with Python, MATLAB, or similar scientific programming environments. Ability to work with large datasets, develop reproducible workflows, and apply modern data science tools
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of practical interest, ideally with a focus on Intelligent Energy Systems. This should be demonstrated by a relevant MSc thesis or publications. Familiarity with good software engineering practices and Python
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coding in C++/Python/Julia and/or using software such as COMSOL Multiphysics. You have experience and/or willing to learn hands-on cell testing via electrochemical characterisation (i-V, electrochemical
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extensive experience with performing phylo- and metagenomic analyses; Has extensive programming skills (e.g. Python, R, bash) and experience with HPC; Is able to work in a structured and organized way; Has
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, readiness to participate in interdisciplinary cooperation. Professional command of English. Affinity with computational experimentation in mathematics (Python, Sage, Mathematica, Macaulay2, Gurobi, etc) is a
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). Flexible, readiness to participate in interdisciplinary cooperation. Professional command of English. Affinity with computational experimentation in mathematics (Python, Sage, Mathematica, Macaulay2, Gurobi
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programming languages such as R or Python, or familiarity with other computational tools relevant to genomic and transcriptomic data, or a strong aptitude in developing these skills is essential. Personal
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-up, crystallisation, and advanced analytical methods (NMR, IR, MS, PXRD). (Additional experience with reaction engineering, reactor optimisation, python for data analysis is considered beneficial but
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a similar program. You also possess: Have experience in the construction and empirical calibration of models Possess good programming skills in Python, MathLab, Mathematica, or similar software Good