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. Familiarity with R, Python, Julia, or other relevant computing languages. Experience with register data or other types of big data. Training in application of genetic data. Experience with multilevel modelling
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/fireworks/aflow). Proficiency in at least one programming language for data science and for numerical computing (e.g., Python/Julia/Fortran). We regret to inform that only shortlisted candidates will be
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Experience with force measurement techniques (e.g., AFM, micropipette aspiration) or image-based stress inference methods Solid programming skills (e.g. Python, MATLAB, C+) Exposure to active matter concepts
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data analysis on Matlab. • Developing and using models to characterise the soft robots (both sensor and actuator). • Knowledge of programming (C/C++/python/MATLAB), using a prototyping board like Arduino
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. Degree must have been received within the past five years or anticipated to be received by 5/31/2026. Preferred skills: R, Python, and Microsoft software Statistical analysis tools. Familiarity with ArcGIS
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Proficiency in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with running snowpack and/or numerical climate models on for example High
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variant analysis will be highly regarded (e.g. bulked segregant analysis, mapping population design, whole genome sequencing, long-read sequencing) Experience with R, Python, or equivalent programming
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, including stringent controls, method validation, and troubleshooting in high-variability biological samples. Strong quantitative competence and programming experience (Python and/or R/Matlab) for reproducible
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experience in using statistical and mathematical tools to analyse and interpret soil data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python
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in English. Desired qualifications: Knowledge of computational methods and programming skills (e.g., R, Python). Knowledge of a Scandinavian language may be an advantage for teaching and supervision