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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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Pay Grade/Pay Range: Minimum: $48,600 - Midpoint: $60,800 (Salaried E7) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job
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cardiovascular care using advanced machine learning techniques, including deep learning. Informal enquiries may be directed to Dr. Dimitrios Doudesis, Principal Investigator (Dimitrios.Doudesis@ed.ac.uk
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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of Oceanography at University of California, San Diego). The USGS mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth-system interactions and to deliver
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data to develop a suite of national level vegetation indices capable of long term tracking and monitoring of vegetation quality, density, planting intensity and other suitable characteristics. Although a
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from date of hire. Preferred Qualifications Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 2 months ago
of machine or deep learning models to identify patterns of codon usage in yeast genomes, 2) the implementation of tRNA-sequencing across diverse yeasts and conditions, and 3) the construction of tRNA deletion