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Field
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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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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 15 days ago
Engineering, Computer Science, Applied Mathematics or a related field. - A strong background in image processing or/and in computer vision is required. - Strong programming skills in Python. - Strong
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technologies (such as HTML/CSS, JavaScript, Python, APIs, XML); and modern development workflows (such as Git, CLI, LTI). Must have the ability to understand and follow written and oral work instructions
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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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relevant to medical science and with strong foundations in statistics or machine learning and hands-on Python experience with superior programming skills; prior knowledge of causal inference and clinical NLP
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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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Telecommunications or Computer Science. • Programming skills (preferably in Linux environments, Python, C/C++, React, TypeScript, Node.js, Next.js, D3.js or equivalent). • Knowledge of cloud computing (e.g. AWS
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should have documented background in the following areas: Electrodynamics Data analysis for scientific applications Programming (e.g., Matlab, Python, C, C++) for scientific applications Previous