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central Oxford We are seeking a full-time Postdoctoral Research Assistant to join Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by Coefficient Giving
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning to join Torr Vision Group at the Department of Engineering Science (central Oxford). The post is fixed-term for 1 year
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We are seeking a full-time Postdoctoral Research Assistant to join Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by KAUST and is fixed-term for one
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Classification Title: OPS Research Assistant Classification Minimum Requirements: High School Diploma. Job Description: The Computational Microscopy Imaging Laboratory (CMI Lab), within
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Ref.: 537333 Work type: Full-time Department: Department of Psychology (30200) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Senior Research Assistant/Research Assistant I
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to work both independently and collaboratively in a research team. ● Excellent written and oral communication skills in English. Brief Description of Duties: The Postdoctoral Associate will assist
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We are seeking a full-time Postdoctoral Research Assistant to join the Dynamic Robot Systems Group of the Oxford Robotics Institute and the Department of Engineering Science in central Oxford
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Laboratory of Oceanography of Villefranche | Villefranche sur Mer, Provence Alpes Cote d Azur | France | 12 days ago
: Research assistant Duration: 24 months, spring 2027 Localization: Villefranche sur mer, France Scientific discipline: Marine Volatile Organic Compounds Technical expertise required: Mass spectrometry
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will focus on the processing and analysis of experimental data, as well as the coordination of post-processing activities across research projects. The successful candidate will help define analysis
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researcher to work on systems theory for energy-based learning. What are you going to do? As a postdoctoral researcher, you will develop and analyse new algorithms for energy-based learning of complex systems