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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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-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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among likeminded researchers that also fosters independence and career development. Dynamics of the group build on the CSSM model for distributed and less hierarchical academic collaboration (learn more
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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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(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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the Finnish-language job announcement for further information: https://ats.talentadore.com/apply/tutkijatohtori-sustainable-rural-futures-hanke/m5npoR Department of History and Ethnology The Faculty
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, military service etc.) Excellent/good skills in spoken and written English. English is used as the language of instruction and supervision in this position. Expectations A formal background in bioinformatics
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machine learning techniques, and GPU programming. The simulation results will be compared to observational data obtained using facilities worldwide including ESO and NOT. Who we are looking for A successful
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net period of time, which does not include parental leaves, military service etc.) good skills in spoken and written English motivation for research work in aerosol physics or chemistry. Please note
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resolution by integrating plasmonic nanopores with a high-speed Raman detection system, an automated control system, computer simulations, and advanced Raman-based bioinformatics. The RamanProSeq consortium