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Master’s degree in statistics, data science, machine learning, mathematical modeling, or similar area. Previous experience in working with Bayesian models and their computation and experience in ecological
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with a background in Language Technology, Machine Learning, or Language Typology who are interested in automatic classification and analysis of hundreds of languages to undertake a PhD project exploring
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted