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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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degree in Computer Science, Artificial Intelligence, Data Science, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong
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the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from
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(IDFG) based sources extend deep into the mid-infrared wavelength range with unprecedented spectral coverage (2–11.5 µm). In our lab, we have recently demonstrated a system comprising an in-house built
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an interdisciplinary very active consortium called EVOLF. Job requirements Qualified candidates have a Master in physics, chemistry, engineering, or a related field. Successful candidates are motivated by a deep
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- and electronics- workshops, but also with the NanoLab Amsterdam cleanroom facility situated in the neighboring NWO-institute AMOLF; develop deep-rooted expertise with and maintenance of WZI’s research
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cleanroom facility situated in the neighboring NWO-institute AMOLF; develop deep-rooted expertise with and maintenance of WZI’s research facilities and software packages; be able to act as advisor and expert
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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Join us to explore the mechanics of soft matter through a unique blend of theory, hands-on experiments, and machine learning. Job description Soft matter such as polymers and hydrogels
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) developing and validating preprocessing pipelines; (3) architecting and comparing spectral-only and multimodal (HSI + NIR + Raman + RGB) deep-learning models; (4) implementing robust sensor-fusion strategies