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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
, Python, Unix/Linux command-line tools, and workflow automation Profound understanding of the relevant metrics and methods to analyze microbial communities and functions and their spatio-temporal patterns
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. Proficiency in data analysis software (e.g., R, Stata, or Python). Interest in comparative politics and political economy, preferably in European wage regulation and climate policy. Fluency in English is
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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of the candidate: PhD in the field of Cryptography, Computer security or any related field. Strong publication record in high impact conferences / journals. Very good programming skills (e.g., C, C++, Python
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charge/discharge cycles); Proficiency in languages commonly used in IoT, such as C/C++, Python, and JavaScript. Expertise in firmware development and optimization for microcontrollers and embedded systems
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well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and
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, or a closely related field. Proficiency in analysing large climate and environmental datasets using statistical or programming tools (e.g., Python, R, MATLAB). Capability of both managing research
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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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with process-based models, including APEX, SWAT, EPIC, DayCent, or DNDC. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and
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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data