Sort by
Refine Your Search
-
Listed
-
Field
-
underlying sleep, a fundamental and evolutionary conserved behavior. We are studying the homeostatic and circadian mechanisms regulating sleep, and also have deep interest in understanding the functions
-
algorithms, NLP models, and LLMs to analyze complex data. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and
-
available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
-
neurodevelopment and neurodegeneration of the visual system. Our team applies interdisciplinary approaches, combining multi-omics, genetics, molecular biology, evolutionary biology, viral tools, advanced
-
interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
-
. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow
-
developmental biology, cell biology and evolutionary biology. We like to implement novel omics technologies such as single cell approaches and chemical biology to help us answering our biological questions