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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 1 month ago
, mathematics, and data science. Collaborative projects merge traditional geographic research with advanced computational methods such as graph neural networks (GNNs) and large language models (LLMs) to explore
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for detailed information about acceptable transcripts A current resume/CV, including academic history, employment history, relevant experiences, and publication list Two educational or professional
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in the Mathematical Institute (https://www.maths.ox.ac.uk/groups/mathematical-biology/infectious-disease-modelling). The postdoctoral researchers will develop data-driven mathematical models and
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biology, super-resolution microscopy, live-cell imaging, multi-omics, and mouse disease models to understand insulin-secretion deficiency and synapse degeneration. (See https://www.mcw.edu/departments/cell
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your application Curriculum Vitae (CV), including a list of selected publications and oral presentations A statement of research interests A brief Statement on modeling, simulation, and/or programming
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
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of relevance: Documented expertise and skills in mathematical modelling of community dynamics is a requirement, and proficiency in statistical time series analyses in community ecology is desirable. Skills in
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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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epidemiology About the School: At the core of the School of Mathematical and Natural Sciences (SMNS) is the opportunity for you to work side-by-side with faculty, conducting authentic research in STEM