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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month ago
autonomy, in microscopy techniques such as live-cell imaging; Good analytical skills, critical thinking, and problem-solver mindset; Knowledge of Python programming language; Excellent oral and written
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imprescindible, se valorará positivamente en el proceso de selección la titulación de Máster y la experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript
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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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requirements of the project. The young researcher (M/F) will contribute to different research aspects on the project: • Study/analysis of cryosphere (cryoconite, ice, sediment, soil) environments and microbiomes
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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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example task for a different role within the research group is here ). A start date of January or early February 2026 is preferred, although later starts can be discussed. To apply, please upload a CV
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and scored: A. Knowledge of Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each
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Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each course) and accredited project