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Field
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
knowledge of artificial intelligence and knowledge of natural language processing. Proficiency in statistical analysis, such as econometrics and machine learning for survey data analysis. Experience with data
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research is open; we are particularly interested in those working in the period between 1900 and the present. Open to scholars with PhDs in Science and Technology Studies and related fields whose research
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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for Quantum Technologies (CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices
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, cluster randomised controlled trials implementation science, data linkage, data science, machine learning and artificial intelligence. In this role, you will have the opportunity to engage in a series of
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 3 months ago
both the NCRC in Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills
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to complete the final exam. Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome