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of statistical physics. Technical Skills: Proficiency in data analysis and modeling. Programming: Mastery of at least one programming language (Python, C++, Fortran, etc.). Experience: A minimum of 4 years of post
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proficiency: Matlab, Python, R, SPM, CONN; Very strong knowledge of neurophonetics, particularly stuttering and verbal disfluencies; Solid background in neuroscience and in the neuropsychology of language and
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the performance and sensitivity of a future space mission for cosmology. The candidate will be required to simulate the performance of a specific instrument using Python code in order to predict the sensitivity
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datasets, and strong programming in Python and C. Familiarity with galaxy-redshift survey or 21-cm data analysis is a plus. The successful candidate will join the cosmology and astroparticle team at LAPTh
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highly desirable. The successful candidate should also have experience with data analysis tools (Python and/or MATLAB), and ideally be familiar with the challenges associated with imaging biological
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samples (cell culture) and/or nanomaterials is an asset -experience in scientific programming and data analysis using Python and/or MATLAB -ability to work in an interdisciplinary environment and to
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programming skills in C++ and/or Python; experience with high-performance or real-time computing, e.g. GPU, multi-core, embedded, is desirable Prior experience with SOFA is a clear advantage; experience with
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the main bioinformatics software and methods (R, Python, Bash). Knowledge on large-scale genotyping/sequencing data analyses. Good level in statistics. Good level of written and oral English. Ease in a
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in nanomagnetism and spintronics with emphasis on magnetic skyrmions - Expertise in electrical and MOKE measurements - Expertise in micromagnetic simulations - Experience with Python - Micro/nano
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demonstrate the following skills: - coding in Python - Life Cycle Thinking (LCA, MFA), or spatially-explicit environmental footprinting, applied to mineral raw materials - Knowledge/use of LCA software (e.g