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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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projects in the following areas: underwater vision, multimodal architectures, and computing for responsible AI. Your competencies PhD in computer vision (mandatory) Strong English communication skills
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applications from researchers specializing in probabilistic and neuro-symbolic AI. Areas of interest include, but are not limited to: • Probabilistic machine learning • Deep probabilistic graphical models
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to join our Copenhagen Section. The research profile of the applicant should be within mathematical foundation, verification tools, validation methodologies, probabilistic graphical models and machine
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of novel biostatistical and machine learning methods for healthcare data. Building and mentoring a strong research group in data science methods. Collaborating with clinical researchers and public health
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medical images and other health data. The group develops and evaluates clinically meaningful decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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processing and machine learning, as well as, online control of assistive systems. The PhD position is located in Aalborg, and the candidate will be a member of Neurorehabilitation Systems group at the Health
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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, artificial intelligence (AI), machine learning, and computation have emerged as powerful digital technologies for creatively generating new design ideas and rapidly advancing formgiving methods within