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data or job advertisements, as well as expertise in web crawling, large language models, and text analysis techniques. An excellent understanding of causal inference methods is essential to develop
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: Enhancing the epistemic power of multimodal explanations by incorporating quantitative data collected by sensor technologies Project Introduction: Technological advancements, especially in smartphone sensor
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findings of bibliometric, quantitative, and qualitative data Assist in the preparation of grant reports Qualifications: Must be a registered McGill student Experience with large, structured literature
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processing, integration and visualisation Proven experience developing and using necessary pipelines for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling
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investigating adaptive neural circuits underlying distinct forms of behavioural flexibility. The postholder will be responsible for designing, developing, and operating advanced large-field or multi-brain region
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-enabled control planes and data processing for fibre sensing in optical networks. The work will focus on the development of methods for analysing fibre sensing signatures as well as methods to incorporate
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, effective complexity and logical depth). The data basis for the analyses are two-fold: first, recent connectome data, i. e. large datasets of all synaptic connections in the fly brain based on electron
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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experiment and data modeling approaches. Required qualifications PhD in molecular biology, biotechnology, bioengineering, bioinformatics, chemistry or related fields. 3+ years hands on experience with high