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Field
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and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries. Look at the BSC experience: BSC-CNS
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adopting an integrated and sustainable strategic vision of R&D and training. The institute focuses on various aspects of the mine lifecycle and aims to provide significantly higher added value. In
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(required) Quantitative skills in time‑series analysis, biogeochemical data processing, and uncertainty assessment (R, Matlab, Python, or similar) (Required) Field experience (desired) Excellent English
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the terms of their appointment. Qualifications include a PhD degree or equivalent in biostatistics, statistics or related quantitative field with considerable knowledge and experience using the R software
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data analysis is required. The lab mostly uses R for data analyses; knowledge of R is not required, and the postdoctoral scholar will have the opportunity for mentorship and learning. To Apply: Motivated
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. • Strong proficiency in Python and relevant libraries for data analysis and modelling (e.g., TensorFlow, Keras, Scikit-learn, Pandas); knowledge of R would be an asset. • Familiarity with geospatial data
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Python and R; - Demonstrable experience with Machine Learning; - Excellent problem-solving skills and the ability to work both independently and as part of a team. This position is for full-time, on-site
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statistical and/or multivariate approaches (proficiency in tools such as Python, R, or equivalent is desirable); * Ability to design, adapt, and optimize experimental protocols; * Strong analytical and critical
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in R or Python Desired - evidence of strong computational skills and large dataset analysis - experience with hierarchical Bayesian modeling - expert knowledge of plant functional ecology - fluency in
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neurodegenerative mouse models Experience in developing image analysis workflows (Python, MATLAB, R, Imaris) Experience in histologic post hoc brain tissue analysis (IF, IHC, RNAScope) Experience in antibody