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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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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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processing, or spectroscopy. Familiarity with hyperspectral imaging or related optical imaging methods is an advantage. Strong programming skills in Python and/or MATLAB. Interest in applying machine learning
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processing and hybrid BCI design Machine learning (ML) Bioinspired control systems Neuroplasticity and motor recovery Real-time control of soft exoskeletons Your Role As a PhD candidate, you will: Develop and
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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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research and education towards the integration of advanced medical image computing for supporting computer-aided disease diagnostics and intervention planning. Responsibilities and qualifications In
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of machine learning frameworks Your research will include using models and codes to investigate the optimized design, integration, and intelligent operation of thermal energy storage systems in industrial