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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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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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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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vision models and other computational methods to annotate the data, and verifying the quality of these annotations using human-in-the-loop approaches. In addition to conducting research, the post-doctoral
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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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-edge sensors with current computational tools and machine/deep learning. As a Postdoctoral Researcher, you will be a key member of our team responsible for designing the seamless integration
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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
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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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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
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20 Dec 2025 Job Information Organisation/Company University of Turku Research Field Computer science » Other Engineering » Computer engineering Mathematics » Algebra Mathematics » Applied