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project TARGET-AI will bring together expertise from multiple research groups to advance the state-of-the-art in combining the most advanced techniques from deep learning/AI with rigorous statistical
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, Bioinformatics, Epidemiology, Biostatistics, Biomedical Sciences, or related disciplines; Strong background in statistical modeling, and/or machine learning (any experience in multimodal AI is an asset); Previous
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team
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and next generation sequencing data. Graphical output of data analysis for publication demonstrated experience in statistical analysis and designing computational methods and tools, including prior
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various
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Master in Experimental Psychology, HCI, UX or related fields Experience with research methods in social sciences (e.g., empirical research, experiment design) Experience in statistical methods is
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microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights into these complex interactions. As part of this position, you will have the
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field #experience in quantitative assessments, including statistics and/or crop modeling #proficiency in programming languages for data processing and analysis #strong commitment to inter- and
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statistical methods for modelling and data treatment engage in teaching, innovation and advisory activities in relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching
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position, you must meet the following requirements: Hold a relevant master’s degree or an equivalent higher education qualification in fields such as Computer Science, Artificial Intelligence, Statistics