27 web-programmer-developer-"INSERM" uni jobs at Chalmers University of Technology in Sweden
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motivated PhD candidates who want to enter a doctoral program at the forefront of science. Our PhD students develop abilities to plan, perform, critically review, and present their research. PhD studies
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Application Deadline 10 Nov 2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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are long vector/matrix multicore architectures. The goal of our team is to develop effective runtime and compiler support to program these architectures using the SYCL, OpenMP and OneDNN programming models
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industry, academia, and government agencies. Our mission is to promote and integrate the life cycle perspective into all decision-making processes. We enable skills development and knowledge sharing among
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for sustainable development Has experience in project management Has a good understanding of the life cycle perspective Has basic understanding of Swedish, both spoken and written Merits: Have experience in web
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Doctoral student in Materials Chemistry of Doped Organic Semiconductors in EU Training Network FADOS
Researcher (R1) Country Sweden Application Deadline 6 Oct 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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research within the project and support collaborations with local and national research groups. The position will help you prepare and plan your future career in industry, academia, or other sectors
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Application Deadline 19 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 304--1
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University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous vehicles that are both safe and trustworthy