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), and machine learning techniques to identify new players of plant growth during and after an immune response. You will validate the genetic leads, such as transcription factors (TFs), identified in our
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(e.g. R, Matlab, Python); some experience with (OMICs) data analysis and/or Chemometrics and/or machine-learning, or willing to learn; a strong motivation to work in a multidisciplinary international
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Center (NPEC) . You will utilise modelling, genetic mapping, and machine learning techniques to identify genes controlling the growth during and after an immune response. In the second phase of the project
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The rapidly evolving field of AI offers promising solutions to the literature screening challenge using machine learning models, like active learning, and, very recently, large language models (LLMs). However
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to the literature screening challenge using machine learning models, like active learning, and, very recently, large language models (LLMs). However, many of these AI-driven solutions emerge from tech companies