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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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planetary science instruments The Post Doc candidate must have experience in Python programming The Post Doc candidate must be eligible to be able to join the NASA Mars 2020 Science Team. The Post Doc
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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have experience in Python programming The Post Doc candidate must be eligible to be able to join the NASA Mars 2020 Science Team. The Post Doc candidate must be eligible to obtain a “restricted” security
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MATLAB or Python) Desired qualifications: The ideal candidate should have: Demonstrated knowledge of fluid dynamics Experience with anisotropic viscous flow Experience with ice texture formation Skills in
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to work independently and collaboratively in multidisciplinary teams Desired qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput
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experience with designing experimental studies and analysing quantitative data. Proficiency in either R or Python. Favourable qualifications (not requirements, but give applicants an advantage): Relevant
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qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Familiarity with
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commonly used programming languages in the field (Python, MATLAB, IDL, Fortran, etc). Prior experience working in the field or other high stress environments. Outgoing and eager to work in a team setting
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with designing experimental studies and analysing quantitative data. Proficiency in either R or Python. Favourable qualifications (not requirements, but give applicants an advantage): Relevant