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traits. A NIDA-funded study concentrates on cannabis use genetics and PRS prediction of response to THC in a laboratory paradigm, and an NIMH study focuses on depression and anxiety genetics in large
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multimodal data analysis. Over the past decade, our institute has pioneered exome and genome sequencing in order to map the genomic landscape of male infertility, particularly focusing on non-obstructive
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ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability to work in a multidisciplinary, highly
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Analyse and interpret time series of environmental monitoring data, and physical/ chemical parameters from tree rings Apply and further develop signal-processing and data-analysis methods Identify
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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
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of large data sets. Determining fundamental and technical limits of a measurement, using principles such as the Cramer Rao bound and Fisher information, Gaussian process, Kalman filter, and state estimation
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is engaged in several metabolite discovery campaigns involving mining of large-scale metabolomic datasets to discover novel metabolites associated with human disease, genetics, and dietary exposures
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priorities, such as Sustainability, Digital transformation and Circular economy, through the execution of five Strategic Research Programs: Data Science for Tires, Tire as a Sensor, End-of-Life Tire
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-particle cryo-EM (sample prep, data processing, model building) is a plus • Expertise in protein expression/purification, especially large multi-subunit complexes • Background in cilia biology, membrane
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the interface of computational biology, molecular science and translational medicine, generating large multi-omic datasets that require robust, reproducible analysis to identify rare signals with high accuracy