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field data, organising datasets, performing statistical analyses, creating scientific graphs and contributing to scientific writing. PI: Andrea Antón Gamazo Funding body: 7324 Institution: Universitat de
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cover letter, attached as the first page of your resume, describing how your experience meets the job requirements of this posting, is required for consideration of this position. Please visit http
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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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, and Jupyter Notebooks; Advanced in NLP, text mining, and graph analytics, including the use of NLTK, spaCy, TextBlob, VADER, and transformer-based models (e.g., BERT, GPT); Familiar with social network
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. Responsibilities Data management and analysis, including omics analysis Assist with and review presentations, manuscript, tables and graphs for accuracy and quality. Review of the literature and interpretation
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, and EHR data. Experience with modern deep learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, and SciPy. Familiarity with convolutional neural networks (CNNs), graph
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 2 months ago
for the Research Group Multidimensional Omics Data Analysis: PhD Candidate (m/f/d) You will be responsible for Setting up a knowledge graph in neo4J for microbiome research Integration of microbiome research data
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researcher to conduct education and research related to the development of AI-based subseasonal-to-seasonal prediction models. https://www.jst.go.jp/k-program/program/kaiyou4.html [Work content and job
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-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex
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for analyzing how landscapes evolve over time. This thesis is part of the ANR GEvoK (Geographic Entities Evolution in Knowledge Graphs) project, which aims at automatically detecting and semantically