9 modal-analysis-machine-learning Postdoctoral positions at Umeå University in Sweden
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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, aiming for a concentrated process gas suitable for carbon capture and utilization or storage. We are now seeking a postdoctoral researcher who will work on sampling and analysis of products from several
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radioisotopes to track sources and ages of different carbon components. The postdoc will lead the acquisition and analysis of aquatic water chemistry data, collected in different Arctic settings such as northern
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organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment
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publications and conference presentations. Maintaining clear, well-documented, and reproducible analysis workflows is essential to the role. Eligibility A person who has been awarded a doctorate or a foreign
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. Importance will also be placed on experience of qualitative methods for data collection and analysis. Given the character of the research project importance will also be placed on good knowledge of both
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experiments, samples from world-unique CO2 experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments