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equivalent in Mathematics, Computer Science, or Statistics Proficiency in one or multiple programming languages (R, Python, Julia, MATLAB) Interest in infectious disease dynamics, public health, global health
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- Good PC and programming skills (e.g., with Python, MATLAB) - Experience with measurement techniques and field measurements using sensor technology (ideally using seis-mometers, geophones, etc.), as
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numerical analysis and partial differential equations, and you have experience in scientific computing or programming (e.g., Python). Knowledge of uncertainty quantification or inverse problems is welcome but
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English. Solid programming skills in Matlab, Python, or C/C++. Great emphasis will be placed on personal qualities such as strong collaboration and communication skills with other researchers and project
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are looking for an enthusiastic individual with a degree in a quantitative discipline. Experience of geospatial analysis (with GIS) is essential and programming with code (e.g. R, Python) would be advantageous
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tasks would be: Develop and implement Python scripts for the automated control of electron microscopes; design and execute automated experiments, including real-time feedback loops between acquisition and
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science, or a related field. Strong background in quantitative methods and statistical analysis. Experience with computational tools for large-scale data analysis (e.g., Python, R, SQL). Familiarity with
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. Preferred Qualifications Knowledge of aging-in-place, accessibility, or universal design. Experience with AR/VR tools, programming/coding (Python, R, Unity, or JavaScript), or community-engaged research
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data, quality assessment/filtering, alignment and variant detection. Experience with long-read (PacBio/ONT) NGS sequencing, genome assembly and annotation Strong competence in programming (shell/python/R
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(e.g. Python, MATLAB or equivalents); Interest in applied thermodynamics, numerical simulation and sustainable energy systems. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7274-SILLAS