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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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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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The Department of Medical Biosciences, Umeå University, Sweden, is offering a postdoctoral scholarship within the project “Developing computational tools for large-scale human intracellular
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econometric methods for analysing large datasets. Are proficient in coding and data management using tools such as Stata, R, or Python. Have a strong interest in the research area and have a strong independent
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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
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, reinforcement learning, robust or explainable models). • Knowledge of Network Digital Twin concepts. • Experience working with large, real-world datasets and building reproducible pipelines (data quality, missing
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extensive use of surface science methods and also includes the most advanced methods of microscopy through its collaboration with VISION. Visiting large scale facilities such as synchrotrons for EXAFS and
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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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. Within this project, work package 1 focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify
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computational methods for analysis and interpretation of large-scale biological datasets. Experiences in structural homology modelling is not essential but would be advantageous. The post holder will work in a