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for the next generation of particle physics experiments and also explores other ways AI can accelerate scientific discovery. The group collaborates closely with computer scientists, astrophysicists and
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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approach to develop chemical probes, investigate biological mechanisms, and evaluate in vivo efficacy. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR
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A postdoc position is available in the lab of Dr. Taosheng Chen Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab ( https://www.stjude.org/research/labs/chen
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
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of the following: Ecosystem Modeling, Machine Learning, Microbiome, Microbial Ecology, Soil Science, or Computational Biology. The positions are for several different projects, including the following: (P1