47 machine-learning "https:" "https:" "https:" "UCL" Postdoctoral research jobs in Finland
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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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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
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. The initial salary is €4064, and the contract includes occupational health care. Our vast array of professional development opportunities means you will grow and learn, having the chance to participate actively
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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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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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the University of Helsinki and living in Finland, please see https://www.helsinki.fi/en/about-us/careers . A diverse and equitable study and work culture is essential to us. That is why we do our best to promote
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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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of Computing The Department of Computing educates professionals for the modern digitalised society. Central themes of teaching and research include Digitalisation, Machine Learning, Autonomous and Intelligent