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Your position We are seeking a highly motivated postdoctoral researcher to join our interdisciplinary team. You will develop and apply advanced statistical and causal inference methods
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mass spectrometry Hands-on use of a mass spectrometry instrument for biomolecular characterisation, data analysis and interpretation Bioinformatic data analysis using statistical software packages
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to have a doctoral degree from an established University, preferably in public health, health sciences, social sciences, or statistics, with advanced quantitative research skills and strong understanding
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. Requirements PhD in Education, Psychology, Child Development, Statistics, or a related field. Strong experience in quantitative data analysis, preferably in secondary data analysis of large-scale datasets and
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. The fellow will also have opportunities to contribute to study design and grant development, including work related to emerging interventional studies. Responsibilities Lead epidemiologic and statistical
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processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; Work on sleep datasets
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data analysis capability, including experience with statistical software such as R or Python. Soft Skills: Strong academic writing, teamwork, and communication skills. Track Record: Evidence of academic
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using integrated measurement, modelling, and statistical approaches. The team works across multiple spatial scales to understand how environmental exposures affect human health and to generate scientific
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, economics, sociology or a related social science, plus strong quantitative capability, you’ll have the opportunity to apply advanced statistical and econometric methods, publish impactful research, and
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emerging interventional studies. Responsibilities Lead epidemiologic and statistical analyses of longitudinal and high-dimensional microbiome datasets Apply and develop methods for multi-omic data