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Field
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. Lead and conduct research projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data
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deadline 15 May to 15 June for the summer semester next year 15 November to 15 December for the winter semester next year Please apply via e-mail only, provided that all requirements are fulfilled (see
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Degree PhD Learning Sciences (alternatively Dr phil, Dr rer nat, Dr med; not recommended for international students) Course location München Teaching language English Languages Courses are held
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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willingness to learn new technologies, and the ability to translate research into high-quality outputs. Where to apply E-mail geogsekr@savba.sk Requirements Research FieldGeographyEducation LevelPhD
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of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user skills, including MS Office and other programs e.g
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-haves: Completed Master's/Diploma degree in the field of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user
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), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack
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-haves: Completed Master's/Diploma degree in the field of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user
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training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure