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intelligence algorithms). Work in a BSL-3 facility is essential to the work of the lab and includes but is not limited to experimentation with the pathogenic bacterium Mycobacterium tuberculosis. BSL-3 work
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an interdisciplinary and international environment. Candidates should send their applications by April 30th through https://cv.newton-6g.eu/ Incorporations will begin in May 2026. DC1: Data-driven models for CF networks
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associate will participate in the design and implementation of the reference data model to ensure simulation system interoperability. Additionally, they will develop AI algorithms and multi-criteria
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» Algorithms Mathematics » Applied mathematics Researcher Profile Recognised Researcher (R2) Application Deadline 6 Mar 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable
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Number AE2026-0029 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0029.pdf CALL FOR GRANT
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testing novel MOF materials for applications in carbon capture (https://doi.org/10.1016/j.xcrp.2022.101063). Successful candidates must have a background in MOF synthesis and characterization. Special
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existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a flexible
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components and control algorithms for the printing process that take into account our theoretical understanding of the processes occurring and utilizing high-speed in situ data acquisition to respond
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satellite communications. Fields of applications range from 5G/6G telecommunications to satellite-based internet connectivity. For details, you may refer to the following: https://wwwen.uni.lu/snt/research
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for the Advancement of Surgery) initiative. The Research Associate will be responsible for developing machine learning algorithms and creating predictive models. The ideal candidate must demonstrate a robust background