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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a
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data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written proficiency in English. Excellent communication skills, ability
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, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 19 days ago
include advancing foliar trait retrieval algorithms, atmospheric correction over dense humid tropical canopies, machine learning and dimensionality reduction for handling big data, landscape evolution
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely related field) with significant post-qualification research experience. You will experience
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biosafety level 2 (BSL2+) lab), immunology (such as flow cytometry and CAR-T engineering), molecular biology (such as CRISPR, RNA biology), or animal models, (e) collaboration with other researchers both
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration CfAI is a large research group in the Department of Physics at Durham University
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computing, high-performance computing (HPC), or machine learning (ML) Interest in Standard Model measurements and/or searches for new phenomena Application Review Review of applications will begin once the
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phasing in humans and other species. In this project, we aim to develop machine learning models to advance the characterization of genetic variations. Research project 3. De novo genes are genes that arise