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Field
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Vacancies Postdoc position on reinforcement learning on real-time image/video processing for medical robot Key takeaways In this role, you will be responsible of developing cutting-edge deep
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and
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demonstration Coordinating cleanroom processes Preparing and maintaining documentation, consolidating results, and interfacing with project stakeholders Presenting research outcomes in progress meetings
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for defect detection and process optimization of tissue constructs (based on biomaterials and living cells), including their efficient deployment on embedded hardware, as well as the design and management
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platform, contribute to accelerating the realisation of PEDs? How can standards (e.g. in terms of data models and APIs) support this process, e.g. by streamlining data retrieval, integration and usage? How
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degree in a relevant field (e.g., transportation, human-computer interaction, cognitive science, mechanical engineering, or related disciplines). Solid background in XR technologies and skills in
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. . Additional information If you would like more information about this vacancy or the selection procedure, please contact Carlo De Servi, via c.m.deservi@tudelft.nl or . Application procedure Are you interested
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during the first five years in the Netherlands. Selection process For more information about the position, please contact Prof. dr Liesje Mommer, via +31 6 20921336 or email: Liesje.Mommer@wur.nl
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develops and analyses behavioural experiments (reaction times, eye fixations) and EEG data. The computational strand simulates behavioural and neural data related to processing and memory retrieval. As a
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for 1.5 years, and will be embedded within the UMC Utrecht AI-Lab initiative. Your primary focus will be the development of AI models for defect detection and process optimization of tissue constructs