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Studierendenwerk Bonn (further information: https://www.studierendenwerk-bonn.de/en/accommodation/ ). For more information on housing in Bonn, please visit our website: www.uni-bonn.de/en/university/university-life
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit
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University of California, San Francisco | San Francisco, California | United States | about 9 hours ago
duties will include 1) routine pre-, peri- and post-operative animal care including documentation; 2) assisting with all large animal procedures, 3) record keeping, data acquisition, and sample collection
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. DESIRABLE EXPERIENCE Ecosystem monitoring and vegetation indices. Time-series analysis of environmental or satellite data. Cloud-based geospatial computing and large-scale data synthesis. CONTRACT DETAILS
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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the day) to accommodate your needs. Working remotely is possible for up to 1 day/week. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus, Oxford
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The Pathology Department is seeking a Biostatistician who will analyze large scale, longitudinal data. Analyzed data is abstracted and extracted from electronic health records, laboratory and pharmacy databases
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conducting research using large-scale routine or registry data, preferably in cancer. High-level proficiency / experience developing reusable analytical pipelines or modular code (in R, Stata, or Python) with
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-funded DECIPHER-M consortium (9 partners, €9M), we are building multimodal foundation models that integrate imaging, text, and structured clinical data to predict metastasis risk and identify tumor origin
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. AI4GI develops tailor-made neural network architectures, including sparse and biologically informed models, to predict disease risk and complex quantitative traits from large-scale genomic data such as