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& facility Assistant professor Associate professor Education EngD Finance HRM IT Lecturer Legal staff Management Marketing and communications PhD Policy and staff PostDoc Professor Research, development
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-performance chain; therefore, enabling stability and control of novel manufacturing processes as well as achieving desired properties within materials science and engineering. Use-cases will be defined within
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from
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Purdue University, Department of Physics & Astronomy Position ID: Purdue -Department of Physics & Astronomy -POSTDOC [#30326, 38314] Position Title: Position Type: Postdoctoral Position Location
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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relevant field, such as Food Safety, Data Science, Food Science, Biotechnology; experience in predictive modelling and quantitative microbial risk assessment approaches; experience with relevant software
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Mongolia Application Deadline 30 Sep 2025 - 16:00 (Asia/Ulaanbaatar) Type of Contract To be defined Job Status Negotiable Hours Per Week 4 Offer Starting Date 15 Oct 2025 Is the job funded through the EU
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 1 hour ago
kernel is currently out of reach, focusing on memory safety in drivers -- which typically interact with the kernel through well-defined interfaces -- offers a promising and tractable target for formal
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? The Villum Investigator group will (eventually) consist of three postdocs, three PhD students and will be part of the section for Theoretical High Energy Physics, Astroparticle and Gravitational Physics
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or experience in strong collaborations and interdisciplinary work at the intersection between machine learning, geophysics and acoustic data modeling. A strong experience with software defined radio Automatic