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artificial intelligence methods. PhD position in atmospheric corrosion studies via novel experiments and machine learning Reference code: 50134137_2 – 2025/MO 1 Commencement date: as soon as possible Work
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aspect of building inclusive and sustainable cities. However, in many cities, disparities in transportation access and its urban impacts persist, reflecting deep-rooted inequalities. Complexity arises in
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/or spatial multiomics, advanced imaging, iPS cells, machine learning, and computational biology. The ideal candidate will have a passion for addressing fundamental questions in biology and an eagerness
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and cutting-edge teaching methodologies. We are currently starting an innovative project that leverages eye-tracking technology to gain deeper insights into how medical students learn and to enhance
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of spoken and written English, communication skills as well as team spirit are essential. German language skills are not a requirement, but a willingness to learn is desirable. As the project involves work
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opportunity to: Gain important insights into clinically relevant aspects of cancer development and therapy Perform state-of-the-art in vivo experiments and large-scale drug and genetic screens Learn and apply a
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relevant aspects of cancer development and therapy Perform state-of-the-art in vitro organoid and in vivo experiments with single cell readouts Learn and apply a wide spectrum of genetic, molecular and cell
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-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this project, we highly
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possible to train a machine learning model to identify tumor-reactive T cells infiltrating any tumor type, cutting months off the time it takes to develop personalized cell therapies for patients. We
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materials science, physics, chemistry, electrical engineering (or a similar discipline) with focus on sensorics; experience in data processing and machine learning; experience in 2D materials synthesis and