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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning
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biology, multiomics and single cell methodology to drive projects focusing on modelling leukemia and immune cell dynamics with the goal to develop new personalised medicine approaches. As our new
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organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning and artificial intelligence methods, targeted validation
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campaigns or model SOA formation and deposition processes. The main duty of the Postdoctoral Researcher is to conduct research related to the project and to report results in international scientific
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volumes of audiovisual data is essential. The appointee must have solid skills in programming and working with libraries for training and using machine learning models. Previous experience in managing large
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communication Demonstrated track record in scientific writing and publishing We also appreciate the following know-how and experience in: Experience from machine and deep learning data analysis Experience from