2,967 software-defined-network-phd Postdoctoral positions in Ireland-University-Ranking-2024
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to PhD level in an area related to Computer Science, the applicant will be proficient in software development, systems administration, networking and cloud. This is an invaluable opportunity to develop
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important pathogens. About you The successful candidate will develop and apply genome analysis pipelines to identify potentiating mutations and/or gene gains on projects across the IOI and PubMLST network
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with the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and
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of data and software used and developed in the project. Contribute to reporting and project management, including participation in project meetings. Publish your research results in peer-reviewed
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method. The salary is expected to be paid until 30 March 2027. Requirements: - A PhD degree in Physics or in related fields, - RESPONSIBILITY for the individually defined project, - Strong interest in
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, including appropriate data and software management. Desirable criteria 1. Experience with tensor network algorithms, Pauli propagation, exact diagonalisation or other classical simulation methods for quantum
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. Research results are often deployed as widely used open-source software and services. The lab’s work is supported by a portfolio of federal and foundation grants spanning biomedical knowledge integration
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concerns applied science for and often with public and private partners. Job requirements We are looking for a highly motivated researcher with: A PhD in a relevant discipline, such as urbanism
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at the interface of macroecology, biodiversity modelling, global-change ecology and restoration science. Your profile Applicants must hold a PhD or have submitted a PhD thesis before the starting date, in ecology
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification