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evaluation protocols for prototype materials and early manufacturing. Collaborate across functions (quality, regulatory, clinical, engineering) to drive materials integration into functional medical devices
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experience with computer modelling, (e.g. agent-based modelling), as well as good grasp of machine learning, forecasting techniques, scenario planning, optimisation, Python and GIS. Good knowledge of English
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computer skills (MS Office, SAP, etc.) enable you to work efficiently Experience in the areas of event management and communication, and an affinity for technical applications and web CMS With your
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afterwards. You will work closely with our research team to implement a new version of our RAG-based chatbot. Profile The ideal candidate will be a computer or data science student, or a student with extensive
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of regenerative medicine, robotics, and medical devices/bionic technologies. Job description As Robotics Machine Learning Intern, you will occupy a pivotal role in the development and design of our future robotic
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the eDIAMOND project, namely: Distributing model training and inference over a network of resource-constrained devices. Online, context-aware adaptation of Federated Neural Network Architectures based
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, computer engineering and/or computer science towards producing relevant and impactful health-monitoring mobile/wearable solutions, then please apply. The research will be highly collaborative; you should be
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" is used for session stickiness "careerSiteCompanyId" is used to send the request to the correct data center "JSESSIONID" is placed on the visitor's device during the session so the server can identify
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of fundamental knowledge about fracture in soft and slender bodies. Soft materials such as hydrogels and elastomers are increasingly used in engineering applications, from biomedical devices to soft robotics
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, but not limited to, materials science, synthesis, analytical chemistry, electrochemistry, and chemical engineering towards producing relevant and impactful health-monitoring wearable devices, then