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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, Artificial Intelligence, Neural Networks, Computational Biology, Bioinformatics, Biomedical Informatics or a related field. Programming experience in a language such as Python or R. Experience in writing grant
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About the Job: You will be responsible for designing and conducting NIH-funded research experiments pertaining to the role of transcription factor mediated networks to direct the fate of stem and iPS
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lively, open and critical discussion within and across different fields of research a work environment with close working relationships, networking and social activities a workplace characterised by
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of Department. This postdoctoral position will position you at the core of an international network driving research into ecological change in the world’s northernmost ecosystems, allowing you to
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a multidisciplinary team Evidence of strong communication and scientific
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network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic
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immediate policy relevance and impact on international assessments such as IPCC reports opportunities for cooperation with PIK’s national and international network of leading climate & energy research
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methods • Quali-quantitative studies (Actor-Network analysis, Controversy mapping, Netnography) • Mapping and examining gender-focused debates • Semi-structured Interviews with youth in Denmark
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for