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Field
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of upper-limb prosthetic devices. You will develop machine learning methods that combine neural signals with environmental context to enable seamless object manipulation. The objective is to create a
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vision systems, on the consideration of strong constraints on processing times and on the use of machine learning techniques in specific contexts (e.g. embedded targets, little data or explainable AI
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested developing new machine learning methods for precision medicine and
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, and computer vision for high-tech greenhouses. The goal of the LEAP-AI project is to collaborate with this team to design the next generation of autonomous greenhouse control systems and will culminate
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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. An affinity with NLP and/or computer vision would also be welcome. You have experience with empirical research in speech technology, evaluating AI systems, and socio-technical factors of AI. You have an
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Job Description Are you passionate about brain-computer interfaces (BCIs), neurorehabilitation, and intelligent assistive technologies? The Department of Health Technology (DTU Health Tech
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to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and
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science, engineering, physics, mathematics or a similar domain. There is a strong preference for an applicant with a biomedical background. Experience with medical image processing, histopathology, computer vision