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: Framework Development: Design and implement a generative deep learning framework for cross-modal integration and analysis, resilient to distribution shifts. Correlation Discovery: Identify interpretable
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compound known to elicit the umami taste in humans. However, a desire to lower the sodium content of foods coupled with adverse consumer perceptions of this compound has led to the search for alternatives
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-on experience on SARRP and in vivo imaging modalities (CT, IVIS, ultrasound) Expertise in diet-induced fibrosis and surgical tumour models Image analysis, IHC, flow-cytometry Industrial experience with Xstrahl
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) A new project area in the institute is the development of artificial intelligence (AI
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enable cohesive analysis across modalities and length scales. This PhD project is a collaboration between Swansea University and Carl Zeiss, a global leader in microscopy solutions. Both partners
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This project aims to develop outcome measures for early detection of neurodegenerative disorders using artificial intelligence (AI) and various sensing modalities, offering personalised support to
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developing novel MRI acquisition and analysis techniques for human MRI scanners with an emphasis on functional brain imaging. Salary will be commensurate with qualifications and experience. Job
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/nature conservation or a similar relevant field as mentioned above; Sound understanding of forest ecology and biodiversity; Experience or strong interest in big data analysis; Proficiency in programming
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systems and potentially extend their experimental capabilities by integrating deep learning throughout the imaging workflow, from data acquisition to final analysis. As a PhD student in this project, you
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investigate the feasibility of new imaging modalities for situations where currently employed imaging techniques, such as X-ray transmission and backscatter, have limitations. This project will focus