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Field
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one of the following areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or
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follows: Task 1: Generation of a comprehensive database of layer-by-layer images obtained from in situ monitoring of the bioprinting process. This involves the systematic capture, organisation, and
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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing
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17 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Other Engineering » Chemical engineering Engineering » Computer engineering Engineering » Electrical
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and image processing. Prior experience with data fusion, machine learning, or super-resolution methods will be considered an asset. Candidates should be motivated to conduct independent scientific
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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society. We are a major part in implementing the 2030 vision of the Faculty of Medicine, i.e. to become leading within digital health and well-known for doctors and engineers finding solutions together. Our
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Job description You will design, manufacture, test and validate two smart material systems/demonstrators: (i) a catheter for invasive surgery with shape and property morphing and (ii) an assistive
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imaging systems capable of penetrating fog, dust, and even certain solid materials. These systems will deliver detailed, high-resolution imaging in challenging conditions where conventional optical sensors
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, Diffusion Tensor Imaging (DTI), Ultrasound, muscle stimulation, electromyography (EMG), and motion capture. Conducting human anatomical specimen dissection studies to obtain in-vitro data for model