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analytical chemistry, particularly GC-MS analysis of trace volatiles Good communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is
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techniques, herbarium specimen collection, preparation, management and storage. Demonstrated experience with computer database software and portable digital data devices. GIS experience including
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and data workflows using relevant tools (e.g., R, Python, ASReml, mixed models) to interpret complex experimental results and inform selection decisions. Proven ability to design and lead independent
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Canada, the USA, the UK, or New Zealand. Proficiency in Python, MATLAB, or C++, and demonstrated experience in deep neural networks and mathematical optimisation, are essential. A commitment to equity
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Matlab, Python, C++ or other relevant language and experience in deep neural networks. Experience and demonstrable expert knowledge in one or more or the following areas: deep learning; graph neural
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(i.e. python, R) and toolchain (i.e. PyTorch, Tensorflow, Scikit learn, CARET) Experience translating research code into production code is a strongly desired bonus An understanding of how systems
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publications, commensurate to opportunity. Demonstrated proficiency in Python, including data handling and backend development. Demonstrated experience developing applications interfacing with machine learning
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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management and programming languages such as R and Python. Level B Essential Criteria: A PhD in entomology or a related discipline, with at least 3 years of postdoctoral experience. A strong track record in
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knowledge of machine learning as well as a basic understanding of robotic perception systems. Essential skills include proficiency in programming languages such as Python and C++, and some experience with