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to develop objective biomarkers of dietary intake and improve understanding of how individuals differ in their metabolic responses to food. Using large population studies, metabolomics, microbiome analyses
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on large meteorological datasets (from sources such as MSWEP, ERA5 and KNMI) that build on experimental measurements. As a postdoctoral researcher in this project you will: - Develop simulation
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, primarily pigs. Strong analytical skills, with experience from large scale data analysis from microbiome and resistome analyses. Experience from molecular biology work. Strong skills in bioinformatics
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research income generation. You will also have experience in working with large micro databases and grouped data. Experience of independently managing a discrete area of a research project, working in
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in the management, cleaning, and analysis of large-scale financial datasets (e.g. bank-level regulatory data, credit registers, supervisory data, financial market data). Proficiency in at least two of
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, protein-DNA interactions with role(s) of epigenetics and Bioinformatics, Cell culture and transcriptional regulation, Imaging and large-scale data analysis/Bioinformatics, and Epithelial biology. Required
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. The incumbent will join a research group led by Dr. Dena J. Clink to develop, evaluate, and apply quantitative methods for large-scale biodiversity monitoring and conservation. The research will leverage existing
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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of Microbiology and APC Microbiome Ireland in University College Cork. More information on our research can be found on our lab webpage https://www.browne-lab.org/. Please contact Dr. Hilary Browne hilary.browne
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Alzheimer’s disease to develop and/or apply computational approaches to large scale genomic or transcriptomic datasets for identification of targets for early detection, prevention or treatment of Alzheimer’s