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interfacing technologies, musculoskeletal models and personalized rehabilitation interventions. Your core tasks will include: Performing human measurements involving HD-EMG acquisition from lower-limb muscles
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. Integrate this neural information into real-time musculoskeletal modeling using our CEINMS-RT framework . Enable neural control of a bilateral cable-driven ankle exoskeleton in post-stroke individuals during
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DFT modelling, are a plus. Project description and responsibilities The position entails the synthesis of new ruthenium-based photocages. You will be integrated in the MCBIM group (https
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will combine BERT type models and Large Language Model (LLM) to examine research publications and patents, in combination with other unstructured data sources such as policy documents, media, call
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forefront of neuromechanics and assistive robotics. Our work bridges neuroscience, biomechanics, and robotics to develop real-time models of joint biomechanics and adaptive control strategies for wearable
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accounting, developing new and fair business models and markets, and research on various agricultural value chains (e.g. livestock, horticulture and floriculture). Your qualities a Master’s degree with a
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Postdoctoral Researcher in Citizen Science & Societal Engagement for an Inclusive Energy Transition,
models for upscaling of the heat transition", and you will be primarily involved in the Work Package that focuses on "Effective and inclusive citizen engagement and support for scalable PED designs
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or operational questions Creating Power BI reports and dashboards Using DAX in Power BI for calculations and insights Working with existing data models and learning to improve them Being actively involved in
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interventions. Your qualities This position may be the right fit for you, if you: have a PhD in Museology, Heritage Studies, History or a related discipline; have experience with public engagement and curation
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at what you need, and draw up a development plan. This position is a good fit for you if you recognise yourself in the following: PhD in Archaeology or in Computer Science/Data Science with extensive