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modeling are applied. To learn more about the lab: https://www.mdanderson.org/research/departments-labs-institutes/labs/xufeng-chen-laboratory.html The incoming fellow will receive training and conduct
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/10.1126/science.adm8203. 2. Keleş, M.F., Sapci, A.O.B., Brody, C., Palmer, I., Mehta, A., Ahmadi, S., Le, C., Tastan, Ö., Keleş, S., and Wu, M.N. (2025). FlyVISTA, an Integrated Machine Learning Platform
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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
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Researcher to join our team in reimagining how we discover and deploy drug combinations in the clinic. Our work is highly interdisciplinary, integrating high-throughput screening, state-of-the-art machine
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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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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. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR) as models. PXR and CAR transcriptionally regulate cytochrome P450 3A4 (CYP3A4) and CYP3A5-drug
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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standardize large-scale multi-omics datasets and build databases Perform integrative and exploratory analyses of multi-omics datasets and apply machine learning methods to uncover underlying biological
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(data assimilation, machine learning, etc.) Writing proposals / securing external research funding Writing and submitting scientific papers Leading a research group Supervising students Participating in