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/deep learning and image processing/tomography advanced programming skills in Python excellent command of English (written and spoken) Assets: team-oriented mindset with strong communication and
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(required) quantitative skills in time-series analysis, biogeochemical data processing, and uncertainty assessment (R, Matlab, Python, or similar) (desired) excellent English communication skills and the
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- or nanoplastics, online or offline ice nucleation experiments. A good knowledge of programming languages such as Python, R, MATLAB or IGOR is expected. Excellent English skills, both in verbal and written
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automated manner. This includes the development of Python-based control and automation routines, as well as the analysis of large experimental datasets. These characterization techniques may be complemented
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development from spatial transcriptomics data. Activities : – design of a new mathematical method – monitoring and study of publications relevant to the field – programming/coding in Python (Pytorch
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candidates will have: A solid grounding in mathematical or physical sciences Interest in dynamical systems and complex system behaviour Some coding experience (Python and/or Julia) Enthusiasm for working
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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applications. Experience in natural language processing, model evaluation, or experimental design is advantageous. Proficiency in Python and/or R and familiarity with AI/ML libraries or generative AI platforms
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for data acquisition and analysis (e.g., Python or LabVIEW) are highly desirable. After a training period, you will operate and maintain the fast EC-STM system and contribute your own ideas to the project
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well as programming skills (Python required; experience with seismic data processing is advantageous) Initial experience seismic data analysis and/or wave propagation modelling is an asset Willingness to participate in