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modelling infectious disease dynamics, population dynamics or fisheries. Proven experience and ability programming in R or Python. Proven experience and interest in the application of mathematical modelling
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with healthcare data (e.g., EHR, clinical text, imaging, omics). Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases
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LIP - Laboratório de Instrumentação e Física Experimental de Partículas | Portugal | about 2 months ago
of the application period will be admitted. Programming skills (Python, C++), experience in extensive air shower tools, in particular CORSIKA, and knowledge of analysis tools, such as ROOT. Preference will be given
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LIP - Laboratório de Instrumentação e Física Experimental de Partículas | Portugal | about 2 months ago
skills (Python, C++), experience in extensive air shower tools, in particular CORSIKA, and knowledge of analysis tools, such as ROOT. Preference will be given to candidates with a strong background on
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learning, or a related field Strong background in deep learning and statistical analysis Proficiency in Python, R, and deep learning frameworks (e.g. PyTorch, TensorFlow) Strong written and verbal
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. Good knowledge of the topic of Cryospheric Processes is a requirement Proficiency in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with
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experience in a professional context; - Experience in developing software based on JavaScript (ReactJS, NodeJS) and Python; - Experience with the use, integration, and development of APIs; - Experience in
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learning. Experience in scientific programming (e.g., Python and/or MATLAB) and code management tools. Good knowledge of written and spoken scientific English. 5. EVALUATION OF APPLICATIONS AND SELECTION
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world class research Essential Application Experience with one or more programming languages (e.g., Python, R, Matlab, Fortran). Essential Application Motivated and self-assured in taking initiative
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, educational, or demographical outcomes. 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