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Field
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of this annex, as well as to: Programming in Python and R. Statistical classification and machine learning methods: SVM, neural networks and logistic regression. 3.2. Qualification: Official Master’s degree in
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of seismic methods and numerical simulations, Good PC and programming skills (e.g., with Python, MATLAB), Experience with measurement techniques and field measurements using sensor technology (ideally using
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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science or related discipline Experience and skills Experience in developing MLIPs, including good programming skills in Python and C, demonstrated via contributions to code repositories Experience with
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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highly collaborative environment Programmers comfortable processing and analyzing large data sets in Python; experience with C++ (or another low-level language) is a plus Strategic thinkers with
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a strong background in one or more of the following areas: nonlinear (Lyapunov-based) analysis tools, software skills with Matlab or Python, and strong writing skills. Special Instructions
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scientific writing and communication skills very good knowledge of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in
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. Experience with high-throughput data analysis, including single-cell RNA sequencing, spatial transcriptomics, or computational immunology using R or Python, is a plus but not required. Excellent organizational
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Physics 1. Necessary requirements: 1) Ph.D. in the field of physical sciences 2) good programming skills, knowledge of C/C++, Python in the context of physics, knowledge of Linux/Unix 3) scientific