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, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python) are required. Ability to communicate effectively in both
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processing, or networking (preferred). You have strong background in machine learning or deep learning (experience with deep learning frameworks such PyTorch and TensorFlow is a plus). You have solid
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research area MERGE (https://www.merge.lu.se ), focused on climate modelling. Aerosol research has been conducted at Lund since the 1970s and is now a designated profile area at LTH (https://www.lth.se
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The mission of Hidden Valley 4-H Camp is to provide youth with a fun, residential camp experience under the guidance of positive role models that emphasize community building, positive social
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
Python Documented experience with NLP and computational text analysis Experience working with language modelling, semantic analysis, or related machine learning approaches Requirements Documented
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on the development of methodologies and techniques of Evolutionary Computation and Machine Learning. V - Initial grant duration: 3 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial
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and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data (e.g., muti-omics) in biology and medicine for precision medicine via a variety of statistical and
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation