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publications at major machine learning, AI or closely related conferences and journals; and (b) good communication and writing skills in English. Applicants are invited to contact Prof. Qiu Anqi via email at
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. · Knowledge of molecular biology, cell biology, immunology, neuroscience, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning
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, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning, artificial intelligence, or translational biomedical research is considered
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researcher in Computer Science, Data Science, Human-Computer Interaction, Psychology, Empirical Educational Research, Learning Sciences, Cognitive Science, or related disciplines who is eager to contribute
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programming languages. Experience with DICOM data, medical-image registration, high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image
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, chromatin profiling, genomics, spatial transcriptomics and single-cell data. Apply statistical, machine learning, and network-based approaches to analyze high-dimensional biological data. Collaborate closely
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on future long autonomous navigation techniques. About you a PhD in a relevant field or near completion extensive knowledge of robotic navigation, machine learning or other relevant fields experience working
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of metabolism, membrane transport, cellular regulation, structural systems biology, machine learning and disease mechanisms. These positions are embedded in the transition from CeMM in Vienna to the newly founded
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to regulatory agencies, investors, pharma companies etc. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Develop models
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pathophysiological mechanisms for acute organ injury research under POI-KB. · Authorship of high-impact first-author or co-author manuscripts in leading informatics and machine learning journals and conferences