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Field
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quantitative field like economics, mathematics, computer science, or engineering, or related area of study [or 5+ years of relevant coursework or professional research/engineering experience]; 5+ years
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Campus in North Austin. Purpose This position aims to advance innovative processing and acquisition methodologies for land DAS and dense surveys, focusing on synthetic modeling, 4D analysis, and seismic
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in writing grant applications and working with machine learning approaches such as MaxEnt, random forest, neural network. Experience using Geographical Information Systems and ecological niche modeling
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large AI models or their applications. Current PLI projects involve work with language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and
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Medical Director and Associate Resident Clinic Director for the clinic. Apprentice model to get on-the-job training for a future career in educational or administrative clinician leadership. Primary mentor
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balance modeling techniques (see below) with existing datasets of field-observed microclimate measurements (e.g. temperature and soil moisture) under various vegetation structural conditions. Objective 2
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(ADMC), Accelerating Medicines Partnership Program for Alzheimer’s disease (AMP-AD), and Model Organism Development & Evaluation for Late-Onset Alzheimer’s disease (MODEL-AD). Requirements Successful
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Posting Information Posting Number FAE1908 Advertised Title Postdoctoral Fellow in Machine Learning and Computational Biology Campus Location Main Campus (Memphis, TN) Position Number 023825
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hours to a few days) are difficult owing to model and data limitations, the importance of extremes and anomalies, as well as the need to appropriately blend physics with AI. 2. Theme 2 (“Downscaling
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, therefore, experience in working with animal models of disease is required. Knowledge of computational analyses of large data sets is necessary for the work. Supplemental Information How to Apply: If you are