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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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concerned with optimal transport for inverse problems. Optimal transport for inverse problems One of the central topics of the research projects is the further development of theory and methods
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traits – and link these traits to epigenomic variation profiled via whole genome bisulfite sequencing. The candidate will also have the opportunity to explore advanced pangenome-based methods to probe
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to polarization. Leveraging network science, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health
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a doctoral degree in demography, public health/epidemiology, statistical sociology, statistics, population genetics or other relevant field, have strong quantitative methods skills and an excellent
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for green hydrogen continues to rise, the high energy demands associated with conventional methods like electrolysis highlight the need for alternative approaches. Photocatalysis, leveraging solar energy for
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utopia, we aim at developing literary theory’s frameworks and methods in order to bring Eastern-European literary traditions into the world-literary discussion. The project is hosted at the Faculty
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physics and urban meteorology groups at INAR. The computational aerosol physics group uses computational and theoretical methods to understand cluster and particle formation for atmospherically relevant
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research profile in inverse problems and computational mathematics. About the job This project focuses on developing advanced methods for uncertainty quantification in inverse problems, i.e., mathematical
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are required to hold a relevant doctoral degree, for example in health sciences, sport sciences, environmental sciences, or another relevant field. We value knowledge of statistical methods, ability to analyze