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Field
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-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put on discovering biophysical
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demonstrate suitable experience in computer science, machine learning, robotic vision, or a related field (through a high-quality Honours or Masters degree). The successful candidate must be able to enrol as a
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validation with end-users. The student will have access to specialised training in quantum security and advanced machine learning. The self-funded nature of the project affords the unique flexibility to pursue
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, chemistry, chemical engineering, computer science, or a related field. Experience in continuum solid mechanics. Experience with machine learning for scientific applications. Strong programming skills (e.g
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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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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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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-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks that combine principled reasoning with the efficiency of modern machine learning
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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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: 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