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evaluate algorithms for treatment and response matching using integrated clinical and molecular datasets. Develop knowledge graphs and multimodal embeddings for cancer patient digital twin construction. Lead
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not limited to using UAV platforms to characterize active fire thermal and gas emissions, improve spreading models and detection algorithms, and assessing post-fire effects. The aim of the project is to
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has also been developing physics-based machine learning algorithms for three dimensional seismic modeling, imaging and inversion using high performance computation including parallelization on GPUs
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(and other geophysical techniques) forward and inversion modeling. Write professional-level codes/algorithms. Publish quality research results in peer-reviewed publications and presentations. Participate
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using high spatial resolution satellite imagery Exceptional written communication abilities Strong programming experience Familiarity with machine learning algorithms (e.g., DCNN, XGBoost, SVM, Neural
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across the country, is currently building a comprehensive web app and mobile app data collection tool, developing machine learning algorithms to sense psychological states in daily life, and sending
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March 2025, but negotiable. Inquiries about the position can be directed to Kelly Zamudio (kelly.zamudio@austin.utexas.edu ). The University of Texas, Austin has an active group in evolutionary genomics