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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 16 days ago
focus in medical education is considered an asset), including the pursuit of local, national, and international grant-funded research using quantitative, qualitative, and mixed methods approaches
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to the intensional paradoxes. The project is highly interdisciplinary and brings together methods and techniques from philosophy, logic and linguistics. PhD 1 will be conducting research within the Property work
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coding abilities, including skills in statistical analysis (e.g., R), computational methods (e.g., NLP methods), programming (e.g., Python), online research tools (e.g., Qualtrics) Strong interpersonal
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(electron microscopy e.g. EPMA, SEM, and X-ray methods e.g. µCT, XRD) Preparing and evaluating solution analyses using ICP MS/OES Publishing and presenting research results at national and international
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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and mainstream housing and their role in the social care system. We are open to a range of methodological approaches provided that the proposed methods are appropriate to the topic. The project will
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offer additional qualification improvement possibilities. Course organisation The programme is intended to be completed in three years, and it contains method courses, scientific colloquia, PhD seminars
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-resolution microscopy with genome editing and advanced image analysis, we systematically assess how these methods can reveal disease-associated cellular phenotypes at unprecedented spatial resolution. Working