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Field
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experimental data acquisition system (LabView, etc.) and programming skills (Python, etc.) for data analysis would be a plus. Familiarity of cryogenics is not necessary. Intrinsic orientation for research and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
(relevant code may include Python and/or C/C++) understanding of process models and (probabilistic) reasoning techniques understanding of programming language internals (e.g., abstract syntax trees) Languages
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with training and using protein language models or similar experience with non-protein large language models. Expertise in python and machine learning implementations (e.g., pytorch). Expertise in other
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criteria - Computer skills, particularly in Python and C++, are necessary for the development of the analysis software. Knowledge of Git version management software is also desired. - Proven knowledge
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- Polyploidy and genomic instability - Automated image acquisition - Scientific programming (Python, Java, or MATLAB) 4. Soft Skills and Professional Qualities - Strong analytical skills - Scientific curiosity
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. Programming experience (Python, MATLAB) and handling of experimental data. Interest in bio-inspiration, animal cognition, mobile robotics, or autonomous systems. The candidate must hold one of the following
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interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be
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. Additional skills : experience in high-performance numerical simulation; familiarity with variational quantum algorithms and quantum simulation; experience in scientific programming (Python, Julia, C/C
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• Education: Master's degree in Automation, Electrical Engineering, AI, or Energy. • Skills: Modeling (Python/Matlab), AI (PyTorch/TensorFlow), signal processing. • Qualities: A passion for experimentation (HIL
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using Python, Matlab, or equivalent programming languages. Previous experience in interdisciplinary research projects at the interface between engineering, materials science, and biology will also be