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Field
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under varying lighting, fabric blends, and soiling; (5) porting the inference pipeline to an embedded/edge-compute platform; (6) integrating with our robotic pick-and-place cell for iterative field trials
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available (>1.1 million people). The goal is to establish how many archaic human groups contributed to our genomes. Your task is to infer key parameters of the archaic human evolutionary history such as
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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& Analysis Perform quality control, alignment, and quantification of bulk and single-nucleus RNA-seq datasets. Conduct differential expression, clustering, trajectory inference, cell type annotation, and
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derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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Research Assistant/Associate Professor (Proteomics and Bioinformatics), Non-Tenure Track - (220000I3) POSITION SUMMARY Location: On-site at the University of Maryland School of Pharmacy, Baltimore
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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-mechanical phase-field model incorporating hydrogen diffusion, mechanical degradation, and fracture evolution. - Employ physics-informed neural networks (PINNs) to infer hidden fields and accelerate