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, software, or comparable scholarly work. ● Experience developing, adapting, or validating computational pipelines and using version control, high-performance computing, cloud computing, workflow systems
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application! This recruitment is linked to the Impact Innovation program Swedish Metals and Minerals – an initiative of Energimyndigheten, Formas and Vinnova. Read more: https://impactinnovation.se/program
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interoperability with BIM, GIS, and LCA systems through open standards. It also includes mechanisms for data collection, harmonization, cleaning, and quality control using artificial intelligence and machine
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PhD Positions Application Deadline 25 Sep 2026 - 12:00 (Europe/Warsaw) Country Poland Type of Contract Permanent Job Status Full-time Hours Per Week 40 Offer Starting Date 2 Oct 2026 Is the job funded
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at: www.ftf.lth.se , www.nano.lu.se , https://kaw.wallenberg.org/en/research/semiconductor-bandgap-key-future-green-electronics, https://c3nit.se/ Subject description The purpose of this project is to develop a data
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
Framework Programme? Not funded by a EU programme Reference Number 2026-10411 Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD will be hosted by Inria
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technologies, and sequencing quality control metrics is essential. This is an exciting opportunity for a researcher who enjoys working at the intersection of science, technology, and collaborative discovery
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an industrial collaboration with a Swiss industry partner, and the Automatic Control Laboratory (IfA) at ETH Zurich. Planned start date for the position is October 2026. Project background Our research group
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postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Minimum Number of References Required 3 Maximum Number
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence