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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl
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neuroscience institutes (ISC, SBRI, see LABEX CORTEX) provides many opportunities for discussions and training, including regular seminars and different journal and method clubs. English is the working language
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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• Understanding of agricultural production systems in the U.S • Experience working with spatial data and machine learning models. • Strong knowledge of programming languages, such as Python, R . • Demonstrated
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documents, including OCR post-processing and parsing of legacy texts Proficiency in scientific programming (preferably Python), version control (e.g. Git), and data standards such as RDF and Darwin Core
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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different streams. Apply for grant applications that lie in the center’s strategic interest and integrate research and advance the center’s research portfolio. Facilitate Knowledge Integration: Bridge work
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positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
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the analysis of gene expression and neuronal activity across different models, with the ultimate goal of contributing to the development of treatments that could modify the neurodegenerative progression