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strategies such as molecular glues and targeted protein degradation. Our research integrates molecular and cell biology, biochemistry, genetics, and computational approaches to identify and exploit cancer
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dynamics and behaviour, e.g. aerial/drone surveys, line transects, camera surveillance and photo-ID. Experience with Bayesian statistical modelling Proven ability to handle large ecological datasets and
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dynamics and behaviour, e.g. aerial/drone surveys, line transects, camera surveillance and photo-ID. Experience with Bayesian statistical modelling Proven ability to handle large ecological datasets and
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specimens to estimate historical age structures over the last 150 years. Forecasting Shifts in the Pollination Service Window. The researcher will use Bayesian inference (e.g., Integrated Nested Laplace
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/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
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, Micro-C/Hi-C, BS-Seq/EM-Seq), massively parallel enhancer assays (ATAC-STARR-seq), and comparative/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle
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by combining all available data, taking advantage of the varying temporal resolution and different time spans that the records cover. This work will involve Bayesian tools developed by our research
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nanometer CMOS and other related technologies. The target chips include digital signal processors, radio frequency and millimeter wave frontends, data converters, as well as larger systems with a mixture of
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the immunologic role of EVs and how they can be used as biomarkers or therapeutic targets in cancer and lung diseases. Duties The postdoc will work in studies on clinical material from patients with cancer, and how
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technologies. The target chips include digital signal processors, radio frequency and millimeter wave frontends, data converters, as well as larger systems with a mixture of analog and digital signals. Our