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will be conducted in parallel with a sister study in the Canadian Rocky Mountains (a similar position is being advertised at McGill University – see here , Students are welcome to apply to both if they
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simulation pipelines for generating annotated RGB-D data 3D semantic perception: Development of learning-based methods for object detection, segmentation, and scene understanding using RGB-D sensor
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hosts The Intelligent Human-Buildings Interaction (IHBI) Lab an interdisciplinary research hub pioneering novel methods to study interactions between humans and the built environment. The lab
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combines high-throughput screening, directed evolution, and single-molecule biophysical methods, and spans projects from fundamental protein science to translational applications. Project background
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, indicators and survey information. The division combines macroeconometric modelling with data science methods for nowcasting, high-frequency indicators construction, machine learning, time series
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and the mechanisms that enable life to emerge. Developing reliable methods to detect reliable traces of life (biosignatures) – whether through remote sensing or direct on-site measurements – requires
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. You will be a dynamic, creative, and motivated scientist interested in pursuing questions deeply. You will use a range of methods for next generation RNA sequencing, and to integrate data from
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-relevant questions. We work with macroeconomic, microeconomic, firm-level, household, geospatial and international datasets and apply modern econometric methods, including panel-data, time-series and causal
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regions. Job description The research focuses on investigating/developing generic methods and algorithms in the context of multi-modal synthetic aperture radar (SAR) for the estimation of environmental
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chains. In this context, the successful candidate will conduct doctoral research using quantitative and qualitative research methods, including engagement with industry partners and analysis of secondary