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. The project will focus on integrating quantitative and textual information, accounting for structural shifts in measurement processes over time, and developing scalable inference for high-dimensional settings
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development of improved software workflows for biomarker data generation and for geoscience process modeling, conduct field work and synthesize existing data for model calibration and database synthesis, co
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communication skills and an ability to work well in teams You are fluent in written and spoken English You have strong analytical skills You are good at working independently and driving a project You are
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machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods; representation learning; analysing sound sequences and vocal interactions; category discovery; Perma
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of the institution’s BSc or MSc level programmes at the University of Gothenburg or Chalmers University of Technology. You should have good knowledge in English, both spoken and written. You need to be in Gothenburg
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Control Engineering and Instrumentation are growing in importance due to the need for high-quality data and information to monitor, make decisions and take correct actions in almost every process that
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experimental workflows A sound understanding of demagnetisation procedures, magnetic-property measurements, data processing, uncertainty, quality assessment and interpretation Experience with quantitative data
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through publications. Experience of analytical methods such as elemental analysis, spectroscopy (e.g. FTIR), chromatography or thermal analysis (e.g. DSC or calorimetry). Very good command of English
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expertise spanning bioacoustics, engineering, and scientific engagement, and the Macaulay Library of Natural Sound, the world’s largest collection of animal media, including bird recordings from around the
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chemistry W/M. This project focuses on the self-assembly of co-catalysts from photoredox/HAT catalytic processes. It aims to study and develop an innovative supramolecular photocatalytic methodology