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, proteomics, conditional knockout/knockin mice, in vivo and in vitro disease models, and 3D cell printing. Our studies utilize advanced, non-invasive clinical imaging and functional tests (e.g., OCT, OCT
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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. About the role The Kohl lab uses a multidisciplinary strategy, ranging from in vivo calcium imaging and in vivo / ex vivo electrophysiology to behavioural profiling, viral circuit tracing and molecular
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a multidisciplinary strategy, ranging from in vivo calcium imaging and in vivo / ex vivo electrophysiology to behavioural profiling, viral circuit tracing and molecular approaches to investigate
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. Proficiency in programming languages like C and Python, as well as deep learning frameworks such as PyTorch and TensorFlow. Knowledge in imaging and computing device and equipment. Strong communication
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We are seeking a highly motivated postdoctoral Research Fellow to join our interdisciplinary project on how cryogenic OrbiSIMS, a cutting-edge mass spectrometry imaging technique, interacts with
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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and imaging experiments. The group's research is organized around three main themes: the mechanistic modeling of pattern formation and morphogenesis; the synthesis and decomposition of developmental
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eikones - Center for the Theory and History of the Image at the University of Basel The center invites applications from outstanding junior and senior researchers in the humanities, social sciences
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are developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph nodes during breast cancer surgery. The instrument will allow surgeons