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, together with research experience in at least one class of modern generative models, are particularly encouraged to apply. In addition to conducting research, the successful candidate will teach two courses
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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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seeking a highly motivated Postdoctoral Researcher to join the Machine Learning cluster. The position is part of a research project investigating how visual foundation models can efficiently acquire new
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learning and benthic systems. This position offers an opportunity to contribute to cutting-edge research, particularly advancing the use of remote sensing datasets and machine learning for constructing
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segmentation, anomaly detection, and extraction of biomarkers for disease classification. Design deep learning models for multimodal image registration and alignment of ultrasound with ground-truth MRI data. 2
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/2026 Position Qualification Position Summary Developing and/or applying artificial intelligence, machine learning and/or data science-based methods to address cutting-edge topics, including but not
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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and